ML PLATFORMING
TALENT SOLUTIONS
Our expertise in data recruitment uniquely positions us to understand the complexities of Machine Learning Platforming jobs. We recognize the importance of these positions in developing, managing, and optimizing the platforms that underpin successful ML operations.
Our recruitment strategies are designed to identify professionals who are not only skilled in ML technologies but also proficient in creating and maintaining robust ML platforms.
Harnham's extensive global network enables us to tap into a rich talent pool, ensuring access to the best candidates in the ML Platform domain.
Our local market knowledge across the United States, Europe, and the United Kingdom allows us to match your organization with candidates who fit your technical requirements and company culture, ensuring a seamless integration into your team.
WHY
HARNHAM?
Our recruitment strategy is centred on understanding the unique needs and challenges of your organization. We provide a customized approach to ensure we deliver candidates that not only have the required technical expertise for Machine Learning Platforming jobs but also align with your strategic goals and values.
As a leading global authority in data recruitment, Harnham boasts a large team of dedicated specialists who understand the nuances of the ML Platform space.
This extensive network allows us to offer superior recruitment solutions, tailored to the specific needs of your organization, regardless of industry.
With over twenty years in the field, Harnham has a proven track record in data talent acquisition. This experience provides us with the insight to effectively navigate the ML Platform recruitment landscape, ensuring we deliver candidates who can drive your ML initiatives forward.
OUR
SERVICES
As a global leader in data recruitment, our expansive team of specialists offers unrivalled insights and solutions, ensuring we meet the specific needs of your organization, regardless of industry for Machine Learning Platforming jobs.
- Permanent Recruitment: We specialize in identifying long-term talent for your ML Platform team, focusing on candidates who can grow and evolve with your organization.
- Contract Recruitment: Our contract recruitment services offer flexibility, allowing you to adapt to project-specific or interim ML Platform needs with skilled professionals.
- Executive Search: We find industry-leading executives capable of steering your ML Platform strategies towards success and innovation.
Contact us today to explore how our bespoke talent solutions can elevate your organization's ML capabilities.
JOBS
LATEST ML PLATFORMING
JOBS
Harnham are a specialist Data & AI recruitment business with teams that only focus on niche areas.
Senior ML Engineer
£550 - £600
+ Data Science & AI
ContractEngland
To Apply for this Job Click Here
Senior ML Engineer (LLM & GenAI)
UK Remote | Outside IR35
Day Rate: £550-£600 per day
6-Months
This is an opportunity to join an innovative healthcare technology business on a greenfield GenAI and LLM Engineering programme. You’ll play a key role in building production-grade AI systems that support clinical and research workflows, working on LLM observability, RAG pipelines, evaluation frameworks, and scalable ML platforms within a highly data-driven environment.
The Company
They are a fast-growing healthcare technology organisation using advanced machine learning, proprietary data, and AI-driven products to improve preventative healthcare and research outcomes. Their multidisciplinary teams work across machine learning, software engineering, clinical science, and product development to deliver innovative solutions at scale. Operating in a regulated environment, they are investing heavily in the next generation of GenAI capabilities and production ML infrastructure.
The Role and Deliverables
- Build and productionise LLM, GenAI, and RAG-based applications using proprietary healthcare and research datasets.
- Develop observability and monitoring frameworks covering prompts, inference quality, latency, cost, and model performance.
- Create robust evaluation frameworks combining automated scoring, LLM-as-a-judge approaches, and human feedback loops.
- Deliver production-ready RAG and agentic AI workflows with version control, testing, deployment, and rollback capabilities.
- Partner with MLOps, Data Science, and Research teams to ensure AI systems are scalable, reliable, and compliant.
- Contribute to AI platform strategy, including model serving architecture, infrastructure decisions, and GPU utilisation.
Your Skills & Experience
- Strong experience building and deploying production machine learning systems within healthcare, life sciences, biotech, pharma, or bioresearch environments.
- Hands-on experience developing LLM, GenAI, RAG, or agent-based applications.
- Strong Python engineering skills with experience using PyTorch and modern ML tooling.
- Experience with LangChain, LangGraph, LlamaIndex, DSPy, or similar LLM orchestration frameworks.
- Strong MLOps experience including MLflow, model versioning, experiment tracking, monitoring, and production deployment.
- Experience working with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or Databricks Vector Search.
- Cloud experience across AWS, Azure, or GCP, alongside containerisation and orchestration technologies including Docker and Kubernetes.
- Familiarity with Infrastructure as Code tools such as Terraform.
- Experience operating machine learning solutions within regulated or research-led environments.
How to Apply
If you have a proven track record delivering production LLM and GenAI solutions within healthcare, biotech, or research environments, please apply with your latest CV.
To Apply for this Job Click Here
Principal Forward Deployed Engineer – AI
New York
$230000 - $250000
+ Data Science & AI
PermanentNew York
To Apply for this Job Click Here
Principal Forward Deployed Engineer – AI
New York, NY – hybrid, 3 days per week onsite
$230,000 – $250,000 base salary + annual bonus + RSUs
THE COMPANY
Harnham is partnering with a leading global technology business focused on delivering enterprise-grade AI solutions to professional services and large-scale organizations. The company is investing heavily in the next generation of generative AI platforms and is expanding a highly strategic engineering team responsible for deploying cutting-edge AI solutions into complex customer environments.
This is an opportunity to operate at Principal level, combining architecture, hands-on engineering, customer engagement, and technical leadership while helping shape the future direction of an industry-leading AI platform.
RESPONSIBILITIES
- Lead enterprise AI engagements from discovery and solution design through production deployment.
- Architect, build, review, and optimize large-scale AI and distributed systems in customer-facing environments.
- Partner with Product and Engineering teams to convert customer requirements into scalable, reusable platform capabilities.
- Define technical standards across AI architecture, cloud infrastructure, integrations, security, reliability, and operational excellence.
- Develop repeatable frameworks, deployment patterns, and best practices that can be adopted across multiple customer implementations.
- Communicate technical strategy, architectural trade-offs, and business impact to both technical teams and executive stakeholders.
- Mentor senior engineers and contribute to broader engineering strategy and innovation initiatives.
SKILLS AND EXPERIENCE
Required
- 12+ years of software engineering, architecture, or technical leadership experience.
- Demonstrated experience building and deploying production AI/ML systems at enterprise scale.
- Strong expertise in Generative AI and LLM-powered applications.
- Deep knowledge of distributed systems, cloud-native architectures, and enterprise integrations.
- Hands-on software engineering capability with recent coding and code review experience.
- Experience delivering secure, reliable, scalable systems in production environments.
- Strong customer-facing communication skills with experience influencing executive stakeholders.
Preferred
- Experience with agentic AI systems and autonomous workflows.
- Knowledge of Retrieval-Augmented Generation (RAG) architectures.
- Familiarity with AI evaluation frameworks and model performance measurement.
- Background in forward-deployed engineering or customer-embedded delivery teams.
- Experience operating within regulated industries.
- Expertise in AI governance, privacy, security, and compliance.
- Open-source contributions, patents, publications, or conference speaking experience.
BENEFITS
- Highly competitive compensation package.
- Annual performance bonus.
- Equity participation.
- Opportunity to influence product strategy and enterprise AI innovation.
- Exposure to high-profile customer engagements and complex technical challenges.
- Collaborative, high-caliber engineering environment with significant ownership and impact.
HOW TO APPLY
Please register your interest by sending your CV via the Apply link on this page.
KEY TERMS
Principal Engineer | Principal Software Engineer | AI Architect | Generative AI | LLM | Large Language Models | Enterprise AI | Machine Learning | Distributed Systems | Cloud Architecture | RAG | Agentic AI | Forward Deployed Engineering | Technical Leadership | Customer-Facing Engineering | Enterprise Software | Platform Engineering | Solutions Architecture | Production AI Systems | Hybrid New York Jobs | Forward Deployed Engineer | FDE
To Apply for this Job Click Here
Staff AI Engineer
New York
$160000 - $185000
+ Data Science & AI
PermanentNew York
To Apply for this Job Click Here
Location: Remote (United States, Eastern or Central time zones preferred)
Travel: Approximately 10-20% travel for client meetings and team collaboration
Compensation: Base salary range of $160,000-$185,000
Overview
A technology consulting organisation is seeking a senior AI engineering leader to design, develop, and deploy large-scale AI applications for enterprise clients. This role is suited to an experienced engineer who enjoys owning end-to-end solution architecture, guiding technical direction, and delivering production-ready AI systems with a focus on scalability, security, reliability, and operational excellence.
The successful candidate will work across generative AI, agent-based architectures, cloud-native platforms, and machine learning systems while collaborating with engineering teams and client stakeholders.
Key Responsibilities
- Architect and implement advanced AI solutions, including agent-based systems, reasoning workflows, tool integration, and multi-agent environments.
- Design and optimise Retrieval-Augmented Generation (RAG) platforms leveraging embeddings, vector databases, search, ranking, and knowledge retrieval strategies.
- Build and integrate cloud-based AI applications using managed services, serverless technologies, event-driven architectures, APIs, and data platforms.
- Establish evaluation, monitoring, observability, and testing frameworks for production LLM applications.
- Develop backend services and APIs using modern programming languages and cloud-native design patterns.
- Lead technical architecture discussions and provide guidance to engineering teams across AI initiatives.
- Mentor developers and contribute to engineering best practices, standards, and solution design reviews.
- Improve system resilience through fault-tolerant architectures, monitoring, fallback strategies, and operational excellence practices.
- Partner with business and technical stakeholders to deliver scalable AI solutions aligned with client objectives.
Required Qualifications
- 5+ years of software engineering experience with demonstrated success delivering production AI, machine learning, or generative AI solutions.
- Strong experience building agentic AI systems, LLM orchestration frameworks, tool/function calling, and RAG architectures.
- Deep expertise with AWS services, including:
- Amazon Bedrock
- SageMaker
- Lambda
- DynamoDB
- S3
- Event-driven services and workflow orchestration technologies
- Proficiency in Python and Node.js, including API development and cloud-native application design.
- Experience implementing AI observability, evaluation methodologies, prompt engineering, and production monitoring practices.
- Hands-on experience with containerisation technologies such as Docker.
- Strong understanding of distributed systems, scalability, and modern software architecture principles.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent professional experience).
Preferred Qualifications
- Experience designing enterprise-scale AI platforms for multiple business stakeholders or client environments.
- Prior consulting, professional services, or client-facing delivery experience.
- Experience leading technical teams, mentoring engineers, and influencing architecture decisions.
- Familiarity with AI monitoring and evaluation platforms such as LangFuse, LangSmith, or similar tooling.
To Apply for this Job Click Here
Martech Transformation Lead
London
£500 - £600
+ Digital Analytics
ContractLondon
To Apply for this Job Click Here
London | Inside IR35
Hybrid – Minimum 2 days on site
Contract Length 3 – 6 months
This is a high impact transformation assignment for a senior technology leader who can shape the architecture, platforms and data foundations required to enable an AI-driven operating model. You will play a pivotal role in aligning technology, data and business stakeholders while ensuring complex enterprise platforms are ready to support future innovation at scale.
The Company
They are a large, complex organisation undertaking a significant technology and operating model transformation. With a strong focus on data, AI and platform modernisation, they are investing in the capabilities required to deliver more intelligent, connected and scalable customer experiences. This programme sits at the intersection of technology, data and business transformation, making it a highly visible and strategically important initiative.
The Role and Deliverables
- Define and govern the target technology architecture supporting an AI-enabled operating model.
- Develop platform integration strategies and pragmatic implementation roadmaps across enterprise systems.
- Assess technology and data readiness, identifying gaps, dependencies and key architectural risks.
- Coordinate technology, data and platform stakeholders to align delivery across multiple functions.
- Provide architectural assurance and challenge technology decisions to ensure scalable, sustainable outcomes.
- Oversee platform ownership, supplier engagement and governance frameworks within a regulated environment.
Your Skills & Experience
- Strong experience leading complex technology transformation, enterprise architecture or platform modernisation programmes.
- Deep understanding of enterprise architecture, integration patterns, APIs, data architecture and platform ecosystems.
- Strong knowledge of AI and agentic technologies, including the infrastructure, orchestration, governance and data capabilities needed to scale them effectively.
- Proven ability to define target state architectures and translate strategic objectives into practical delivery roadmaps.
- Experience navigating large enterprise technology landscapes and influencing senior technology and business stakeholders.
- Strong understanding of technology governance, security, risk management and architectural assurance.
- Experience managing technology dependencies, supplier relationships and platform ownership responsibilities.
- Exposure to marketing technology ecosystems such as Adobe, Pega, Workfront, Microsoft and related data or AI platforms is highly desirable.
- Ability to engage confidently with senior technology leaders and business executives, balancing technical and commercial considerations.
Please apply below to discuss this contract opporunity further.
To Apply for this Job Click Here
Senior AI Product Engineer II
San Francisco
$192000 - $259000
+ Data Science & AI
PermanentSan Francisco, California
To Apply for this Job Click Here
Senior AI Product Engineer II
$192,000-$249,000 + Equity
3 days/week on-site
Overview
A fast-growing SaaS organization is seeking a Senior AI Product Engineer to develop and deliver AI-powered product experiences. This role focuses on transforming large language model (LLM) capabilities, retrieval systems, and agent-based workflows into intuitive, production-ready customer features.
The ideal candidate combines strong full-stack engineering expertise with practical experience building AI applications. You will work closely with product, design, and AI specialists to create scalable, user-centric solutions that improve complex business workflows through intelligent automation.
Key Responsibilities
- Design, build, and maintain AI-powered product features across the full stack using modern frontend and backend technologies.
- Develop responsive user interfaces that support real-time and streaming AI interactions.
- Integrate AI services, orchestration layers, retrieval systems, and agent workflows into customer-facing experiences.
- Collaborate with AI and machine learning teams to define APIs, output formats, and user interaction patterns.
- Translate sophisticated AI capabilities into practical, intuitive workflows for end users.
- Identify and improve areas where model outputs create usability challenges or inconsistent experiences.
- Build feedback mechanisms that capture user sentiment and output-quality signals to support continuous improvement.
- Implement observability and analytics for AI features, including performance, engagement, completion rates, and user adoption metrics.
- Create reusable components, state-management patterns, and frontend frameworks that accelerate future AI feature development.
- Develop and maintain automated testing strategies across frontend, backend, and AI-enabled workflows.
- Participate in architecture discussions, design reviews, and technical mentorship activities.
Required Qualifications
Experience
- 7+ years of professional software engineering experience delivering production-grade applications.
- 2+ years of experience building AI-enabled product features.
Frontend
- Strong expertise in React and TypeScript.
- Experience building highly interactive user interfaces that manage asynchronous and real-time data.
- Knowledge of modern frontend architecture and state management patterns.
Backend
- Strong proficiency in Python, Node.js, and TypeScript.
- Experience designing and consuming APIs for AI platforms and distributed services.
AI & Machine Learning Applications
- Hands-on experience working with commercial LLM platforms and AI APIs.
- Strong understanding of:
- Prompt engineering
- Context management
- Retrieval-Augmented Generation (RAG)
- Evaluation and quality measurement frameworks
- Structured outputs and response validation
- Familiarity with agent orchestration frameworks and multi-step AI workflows.
Real-Time Systems
- Experience implementing streaming architectures using technologies such as:
- Server-Sent Events (SSE)
- WebSockets
- Streaming HTTP responses
Product & Collaboration
- Strong product mindset with a focus on usability and customer outcomes.
- Experience working cross-functionally with engineering, product management, design, and AI/ML teams.
- Ability to thrive in fast-paced environments with evolving requirements.
Preferred Qualifications
- Experience in governance, risk, compliance, security, audit, or other documentation-intensive enterprise domains.
- Experience with Model Context Protocol (MCP) or similar AI tool-use standards.
- Exposure to retrieval system design and debugging retrieval-quality issues.
- Experience creating review, annotation, or quality-feedback tooling for AI-generated outputs.
- Prior experience establishing engineering standards and mentoring team members.
Work Model / Location / Engagement Details
- Full-time position.
- Hybrid work environment with a combination of in-office collaboration and flexible remote work.
- High degree of cross-functional interaction with product, engineering, design, and AI teams.
- Opportunity to influence both product direction and AI feature strategy within a rapidly scaling organization.
To Apply for this Job Click Here
Agentic AI Software Engineer
Houston
$160000 - $180000
+ Data Science & AI
PermanentHouston, Texas
To Apply for this Job Click Here
Senior Agentic AI Engineer (Full Stack)
$160,000-$180,000
4 days/week on-site
Overview
We are seeking a senior software engineer with a strong full-stack background who has evolved into AI engineering and agent development. This role focuses on building, deploying, and optimising intelligent agents and AI-driven workflows that interact with enterprise systems, data sources, and users.
The successful candidate will have hands-on experience developing production-grade AI applications using large language models (LLMs), retrieval-augmented generation (RAG), agent orchestration frameworks, and modern software engineering practices. This position is centred on designing and building AI agents rather than purely traditional application development.
Key Responsibilities
AI Agent Development
- Design and develop AI agents capable of reasoning across complex business processes and interacting with tools, APIs, and enterprise systems.
- Build intelligent support and workflow automation agents that understand intent, retrieve information, and execute tasks.
- Develop agentic workflows combining LLMs, structured data, business logic, external services, and retrieval mechanisms.
- Create memory, context, and personalisation capabilities to improve agent effectiveness.
- Implement guardrails, monitoring, evaluation frameworks, escalation paths, and human oversight mechanisms.
- Measure and improve agent performance across quality, reliability, latency, utilisation, and cost metrics.
Full-Stack Application Development
- Build user-facing applications that enable interaction with AI-powered experiences.
- Develop modern frontend applications using frameworks such as React, Angular, Next.js, or comparable technologies.
- Create backend services, APIs, orchestration layers, and integration services using Python-based frameworks.
- Translate advanced AI capabilities into practical business applications and intuitive user experiences.
- Own solutions end-to-end from architecture through deployment and support.
Data & AI Infrastructure
- Build and maintain data ingestion, integration, and transformation pipelines.
- Develop and support retrieval-augmented generation (RAG) solutions and enterprise search capabilities.
- Design systems supporting context management, retrieval, memory, and personalisation.
- Integrate AI solutions with databases, APIs, analytics platforms, and enterprise applications.
- Ensure data quality, security, reliability, and scalability across AI systems.
LLM Engineering
- Integrate and orchestrate large language models within production environments.
- Design prompting strategies, retrieval approaches, tool-calling frameworks, and multi-step workflows.
- Build AI-powered capabilities including conversational assistants, document intelligence, semantic search, and workflow automation.
- Evaluate models, architectures, and AI platforms for performance, reliability, business fit, and cost efficiency.
- Establish monitoring and evaluation methodologies for production AI solutions.
Engineering Excellence
- Leverage AI-assisted development tools to improve engineering productivity while maintaining high code quality standards.
- Stay current with emerging AI frameworks, tooling, and industry best practices.
- Implement CI/CD, testing, observability, security, and production monitoring practices.
- Support reliable deployment and ongoing optimisation of AI-enabled applications.
Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
- 8+ years of professional software engineering experience.
- Strong full-stack development experience across frontend and backend technologies.
- Proven experience building and maintaining RESTful APIs and backend services.
- Experience working with data-intensive applications and enterprise integrations.
- Hands-on experience developing AI agents, autonomous workflows, or LLM-powered applications.
- Strong understanding of LLMs, RAG, tool usage, orchestration frameworks, and AI application architectures.
- Experience integrating AI systems with APIs, databases, enterprise platforms, and third-party services.
- Frontend experience with React, Angular, Next.js, or similar frameworks.
- Experience using AI-assisted development tools within software delivery workflows.
- Experience designing agent memory, retrieval, context, evaluation, or reasoning systems.
- Strong understanding of cloud-native application development and deployment.
Preferred Qualifications
- Experience with modern data-platform or lakehouse architectures.
- Experience deploying applications on public cloud platforms.
- Experience with CI/CD pipelines, infrastructure automation, and cloud operations.
- Experience working within agile software delivery environments.
- Experience building highly scalable enterprise applications.
What Success Looks Like
- Demonstrates an AI-first engineering mindset focused on intelligent workflows rather than simple AI integrations.
- Comfortable operating across software engineering, AI, data, and infrastructure domains.
- Balances innovation with reliability, observability, governance, and security.
- Strong product mindset with a focus on measurable business outcomes.
- Effective communicator who collaborates with technical and non-technical stakeholders.
- Thrives in fast-moving environments where requirements and technologies evolve rapidly.
To Apply for this Job Click Here
Senior AI Engineer
London
£75000 - £95000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Senior AI Engineer
£75,000 – £95,000
King’s Cross, London (1-2 days a week in office)
This is an exciting opportunity for a Senior AI Engineer to play a key role in shaping how AI is embedded across a business. Rather than building standalone proofs of concept, you will develop production-grade AI solutions that directly support core business processes, delivering measurable value at scale.
THE COMPANY
They are a well-established organisation investing heavily in AI and advanced technology. With a focus on innovation, they are building scalable solutions that enhance operational efficiency and customer outcomes. Their environment combines strong engineering practices with the opportunity to work on high-impact AI initiatives. You will join a collaborative team where technical expertise and continuous improvement are highly valued.
THE ROLE
As a Senior AI Engineer, you will design and deliver production-ready AI solutions using LLMs and agentic systems, embedding AI into core business processes to drive measurable impact.
Specifically, you can expect to be involved in the following:
- Design and implement end-to-end AI systems that deliver business impact.
- Build and deploy LLM-powered and agent-based solutions from concept through to production.
- Contribute to technical architecture and engineering best practices.
- Develop reusable components, frameworks, and patterns across multiple AI use cases.
- Make informed decisions on models, tooling, infrastructure, and system design.
- Ensure AI solutions are scalable, observable, secure, and production-ready.
- Support evaluation, monitoring, and governance processes for deployed AI systems.
- Provide technical guidance and mentorship to engineers contributing to AI projects.
SKILLS AND EXPERIENCE
The successful Senior AI Engineer will have the following skills and experience:
- Strong commercial experience delivering production-grade AI systems.
- Expertise in generative AI, large language models, prompting, orchestration, and evaluation.
- Experience designing and implementing complex AI solutions across multiple domains.
- Knowledge of agentic AI systems and multi-step workflows.
- Strong software engineering fundamentals, including APIs, system design, and cloud-native architectures.
- Ability to solve problems in evolving and ambiguous environments.
- Experience influencing engineering standards and contributing to technical excellence.
- Exposure to AI platforms, reusable frameworks, LLMOps, or MLOps is advantageous.
- Experience working within enterprise or regulated environments would be beneficial.
BENEFITS
The successful Senior AI Engineer will receive the following benefits:
- Salary between £75,000 – £95,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Manager, AI Architecture
Atlanta
$175000 - $200000
+ Data Science & AI
PermanentAtlanta, Georgia
To Apply for this Job Click Here
Manager, AI Architecture
Atlanta, GA – Hybrid (3 days per week onsite)
$175,000-$200,000 base salary + annual bonus
THE COMPANY
Our client is a leading global consulting and transformation firm helping enterprise organizations leverage data, analytics, and artificial intelligence to drive measurable business outcomes. Their AI and Data practice combines deep technical expertise with strategic advisory capabilities to deliver scalable, production-ready AI solutions across a range of industries.
This is an opportunity to join a high-performing team at the forefront of enterprise AI, working on complex transformation initiatives that bring generative AI, agentic systems, and advanced analytics into real-world business environments.
RESPONSIBILITIES
- Lead the design and delivery of enterprise AI architecture solutions across client engagements.
- Build and oversee scalable AI platforms, agentic workflows, inference pipelines, and API-driven architectures.
- Partner with client stakeholders, engineering teams, and business leaders to translate requirements into robust technical solutions.
- Drive architectural decisions related to AI governance, security, observability, and production deployment.
- Establish best practices for evaluation-driven development, testing, and AI solution lifecycle management.
- Contribute to reusable frameworks, accelerators, technical standards, and architecture documentation that support broader delivery teams.
SKILLS AND EXPERIENCE
Required:
- 8+ years of experience in software engineering, AI/ML engineering, or AI architecture roles.
- Strong hands-on expertise designing and implementing LLM-based solutions, including RAG architectures, function calling, and AI agents.
- Experience with orchestration frameworks and vector database technologies.
- Deep understanding of cloud-native deployment, monitoring, security, and operational best practices.
- Proven ability to make independent technical decisions and communicate architecture recommendations to technical and non-technical stakeholders.
- Experience designing and delivering production-ready AI solutions within enterprise environments.
- Knowledge of responsible AI principles, including governance, privacy, security, and ethical AI practices.
Preferred:
- Consulting or client-facing delivery experience.
- Experience building reusable AI frameworks, accelerators, or platform capabilities.
- Familiarity with emerging agentic AI architectures and modern AI engineering practices.
- Project leadership and stakeholder management experience.
BENEFITS
- Competitive base salary of $175,000-$200,000.
- Annual performance bonus.
- Exposure to large-scale enterprise AI transformation programs.
- Hybrid working model with a collaborative team environment.
- Ongoing learning and development opportunities within a fast-growing AI practice.
- Opportunity to work with cutting-edge AI, GenAI, and machine learning technologies.
HOW TO APPLY
Please register your interest by sending your CV via the Apply link on this page.
KEY TERMS
Manager AI Architecture | AI Architect | Generative AI | GenAI | Artificial Intelligence | LLM | Large Language Models | RAG | Retrieval Augmented Generation | AI Agents | Agentic AI | Vector Databases | Cloud Architecture | Machine Learning | AI Engineering | Enterprise AI | Solution Architecture | API Development | AI Governance | Consulting | Atlanta Jobs | Hybrid Working
To Apply for this Job Click Here
MLOps Platform Engineer
Phoenix
$65 - $77
+ Data Science & AI
ContractPhoenix, Arizona
To Apply for this Job Click Here
MLOps Platform Engineer
Phoenix, Arizona
This is a unique opportunity to build an enterprise-scale MLOps platform from the ground up. Joining a greenfield initiative, you will play a pivotal role in designing and operationalizing the infrastructure, automation, and governance required to deploy, monitor, and scale machine learning models in production. This project offers the chance to shape long-term MLOps strategy while working closely with Data Science and Data Engineering teams to establish best practices across the organization.
The Company
They are a large, established organization undergoing significant investment in data, analytics, and machine learning capabilities. With a strong focus on innovation and operational excellence, they are building modern data and AI platforms to support critical business initiatives. Their teams are committed to creating scalable, governed, and sustainable solutions that enable advanced analytics and machine learning at enterprise scale.
The Role and Deliverables
- Design and build a production-grade MLOps platform using Snowflake and related machine learning capabilities.
- Develop reusable ML pipelines covering training, validation, deployment, inference, monitoring, and lifecycle management.
- Establish model governance standards including versioning, approval workflows, lineage tracking, rollback procedures, and auditability.
- Implement model observability frameworks for performance monitoring, drift detection, data quality validation, and service reliability.
- Build and automate CI/CD processes for machine learning workflows, including testing, release management, and deployment controls.
- Partner closely with Data Scientists and Data Engineers to productionize models and ensure reliable integration with enterprise data platforms.
Your Skills & Experience
- Strong experience building MLOps platforms or machine learning infrastructure in production environments.
- Proven capability designing and implementing model deployment, monitoring, tracking, versioning, and registry processes.
- Advanced Python and SQL skills with experience developing and maintaining machine learning pipelines.
- Experience building CI/CD pipelines and automation frameworks for machine learning systems.
- Hands-on experience with enterprise machine learning platforms such as Snowflake ML, Databricks, AWS SageMaker, or similar technologies.
- Strong understanding of the relationship between data engineering pipelines and downstream machine learning workflows.
- Experience working with cloud platforms, ideally AWS.
- Ability to collaborate effectively with Data Scientists and Data Engineers to define requirements and deliver scalable solutions.
- Familiarity with Snowpark, Feature Stores, Model Registry capabilities, or other modern MLOps tooling is advantageous.
- Experience with medallion architectures, ML observability, AI agents, containers, dbt, Splunk, or near real-time machine learning environments would be beneficial.
How to Apply
If you are an experienced MLOps Platform Engineer who enjoys building scalable machine learning platforms from scratch and driving best practices across enterprise AI environments, please apply today.
To Apply for this Job Click Here
Engineering Director
London
£120000 - £135000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Engineering Director
UK Remote
Up to £135,000 + 15% Bonus
This is an excellent opportunity to join a newly established Data Hub function and play a leading role in shaping the future of enterprise data and AI. You’ll combine strategic leadership with hands-on technical oversight, helping build a scalable data platform that will support business-wide decision making and innovation.
The Company
They are investing heavily in their data capabilities, bringing previously fragmented data environments together into a single, governed platform. With strong backing from senior leadership and a clear roadmap in place, the Data Hub is a key strategic initiative designed to enable analytics, operational efficiency, and future AI use cases.
The Role
You will lead the Data Hub engineering team, owning delivery, technical direction, and team development.
Responsibilities include:
- Leading and mentoring data engineering teams
- Driving delivery of a modern enterprise data platform
- Owning architecture and technical decision-making
- Consolidating legacy systems into a scalable, governed environment
- Partnering with business and product stakeholders
- Managing distributed engineering teams and delivery processes
- Establishing engineering best practices across Agile, DevOps, quality, and reliability
- Contributing to the wider data and AI strategy
Your Skills & Experience
- Strong people leadership within data or platform engineering
- Deep Snowflake and DBT expertise
- Experience delivering large-scale data platform programmes
- Strong SQL and Python skills
- Data architecture and governance experience
- Agile delivery leadership
- Excellent stakeholder management and communication skills
- Experience leading offshore or distributed teams
- Hands-on technical credibility
Desirable:
- Databricks
- AI/ML platforms and workflows
- Agent-based AI solutions
- Backend or full-stack engineering exposure
What They Offer
- Up to £135,000 base salary
- 15% annual bonus
- Fully remote working in the UK
- Opportunity to build a newly formed Data Hub function
- Significant influence over platform strategy and architecture
- Exposure to modern data and AI technologies
- Clear growth and leadership opportunities as the team expands
To Apply for this Job Click Here
Lead AI Engineer
London
£95000 - £115000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Lead AI Engineer
£95,000 – £115,000
King’s Cross, London (1-2 days a week in office)
This is an opportunity to lead the design, architecture, and delivery of production-grade AI systems that create measurable business impact. You will work on high-value initiatives, building scalable AI solutions that are embedded directly into core business processes rather than standalone prototypes.
THE COMPANY
They are a well-established organisation investing heavily in AI innovation to transform business operations and deliver long-term value. Their focus is on deploying practical, scalable AI solutions that support real workflows and business outcomes. You will join a technology-driven environment where engineering excellence, collaboration, and innovation are highly valued.
THE ROLE
As a Lead AI Engineer, you will
Specifically, you can expect to be involved in the following:
- Own the technical direction, architecture, and implementation of AI systems end-to-end.
- Design and build LLM-powered and agent-based solutions from concept through to production.
- Establish engineering standards, reusable patterns, and scalable frameworks across AI initiatives.
- Make key decisions on models, tooling, infrastructure, and system design.
- Ensure AI systems are robust, observable, secure, and production-ready through effective evaluation, monitoring, and guardrails.
- Provide technical leadership and guidance to engineers working on AI projects.
SKILLS AND EXPERIENCE
The successful Lead AI Engineer will have the following skills and experience:
- Strong commercial experience delivering production-grade AI systems from design through deployment.
- Deep expertise in Generative AI, Large Language Models (LLMs), orchestration, prompting, and evaluation.
- Experience building agentic or multi-step AI systems.
- Excellent software engineering fundamentals across APIs, system design, and cloud-based architecture.
- Ability to define technical direction and operate effectively in complex or evolving environments.
- Experience influencing engineering standards and best practices across multiple projects.
- Exposure to AI platforms, reusable frameworks, LLMOps/MLOps, or enterprise AI environments would be beneficial.
BENEFITS
The successful Lead AI Engineer will receive the following benefits:
- Salary between £95,000 – £115,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Lead AI Ops Engineer (DevOps – GCP)
New York
$70 - $80
+ Data Engineering
ContractNew York
To Apply for this Job Click Here
Lead DevOps / AIOps Engineer
Location: Remote (USA)
Term: 3 Months, extendable
Type: Contract
Hourly Rate: $70-$85/hr (Dependent on Experience)
**we will NOT be engaging with agencies or 3rd parties for this role. No c2c.**
About the Opportunity
Our client is an internationally awarded Data, AI, and Machine Learning consultancy that helps enterprise organizations leverage cloud technologies, advanced analytics, and artificial intelligence to solve complex business challenges. They partner with leading organizations to design and implement scalable, production-ready data and AI platforms that drive innovation and business value.
The team is seeking a Lead DevOps / AIOps Engineer to help architect, automate, and operationalize modern cloud-based data and AI platforms. This role sits at the intersection of cloud infrastructure, data engineering, machine learning, and software delivery, with a strong emphasis on Google Cloud Platform (GCP).
This position is ideal for someone who enjoys both strategy and hands-on engineering, with the ability to design scalable cloud architectures, establish DevOps and AIOps best practices, and help teams successfully move data and AI solutions into production.
Responsibilities
- Lead the design and implementation of cloud-native DevOps and AIOps architectures on Google Cloud Platform (GCP).
- Build and optimize CI/CD pipelines supporting data, AI, and application workloads.
- Develop Infrastructure-as-Code solutions using Terraform and establish repeatable deployment standards.
- Architect and operationalize enterprise data platforms leveraging:
- BigQuery
- Cloud Storage
- Dataflow
- Pub/Sub
- Dataproc
- Cloud Composer
- Build AIOps capabilities supporting the full AI lifecycle, including model development, deployment, monitoring, versioning, and retraining.
- Establish observability across data and AI platforms, including logging, monitoring, alerting, pipeline health, data quality, and model performance tracking.
- Implement secure and scalable cloud infrastructure utilizing GCP IAM, networking, secrets management, and security best practices.
- Collaborate with Data Engineers, AI Engineers, Architects, and business stakeholders to deliver production-ready solutions.
- Define and promote engineering standards around automation, testing, environment management, reliability, and operational excellence.
- Troubleshoot complex production issues and lead root-cause analysis efforts.
- Mentor engineers and provide technical leadership across cloud, DevOps, data platform, and AIOps initiatives.
- Evaluate emerging cloud and AI technologies and recommend solutions that create measurable business value.
Required Qualifications
- 7+ years of experience in DevOps, Cloud Engineering, Platform Engineering, MLOps, or a closely related discipline.
- Strong hands-on experience with Google Cloud Platform (GCP), particularly BigQuery and cloud-native data services.
- Experience designing and implementing enterprise-scale data platforms on GCP.
- Strong understanding of BigQuery architecture, performance optimization, data ingestion, partitioning, clustering, and security best practices.
- Experience with:
- CI/CD pipelines
- Git-based workflows
- Automated testing
- Containerization technologies
- Kubernetes / Google Kubernetes Engine (GKE)
- Strong Infrastructure-as-Code experience, preferably with Terraform.
- Experience with Vertex AI and/or production machine learning platforms, including model deployment and monitoring.
- Hands-on experience with orchestration and data processing technologies, including:
- Cloud Composer / Airflow
- Dataflow
- Dataproc / Spark
- Pub/Sub
- Strong understanding of observability, reliability engineering, monitoring, logging, and alerting.
- Proficiency with Python and/or Bash scripting.
- Strong understanding of cloud security, IAM, networking, secrets management, and enterprise governance.
- Ability to operate at both the architectural and hands-on implementation levels.
- Excellent communication and stakeholder-management skills.
Preferred Qualifications
- Experience with Vertex AI, MLflow, Kubeflow, or other MLOps platforms.
- Experience implementing Generative AI (GenAI) or Large Language Model (LLM) solutions in production environments.
- Experience with Docker and Kubernetes/GKE in enterprise-scale deployments.
- Familiarity with:
- Data Quality frameworks
- Data Lineage solutions
- Metadata Management platforms
- Semantic Data Layers
- Experience working with AWS and/or Microsoft Azure.
- Previous consulting or professional services experience.
To Apply for this Job Click Here
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