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Overview

A large, complex enterprise is seeking a senior data science leader to build and scale its data science function. This role is responsible for translating data into predictive, prescriptive, and AI-enabled insights that improve customer experiences, operational performance, decision-making, and organisational outcomes.
The Director, Data Science will lead teams focused on statistical modelling, machine learning, experimentation, forecasting, optimisation, decision support, and AI-enabled analytics. The position partners closely with data, engineering, product, digital, and business stakeholders to ensure analytical solutions are built on trusted data and deliver measurable value.
This leader will establish best practices for model development, validation, deployment readiness, monitoring, and lifecycle management while fostering a high-performance, innovation-focused culture.

Key Responsibilities

Data Science Strategy & Leadership

• Define and execute the enterprise data science roadmap aligned to strategic business priorities.
• Identify opportunities where advanced analytics, machine learning, optimisation, and AI can improve organisational outcomes.
• Prioritise investments based on business value, feasibility, data readiness, and strategic importance.
• Establish standards for experimentation, model development, validation, documentation, monitoring, and governance.
• Ensure solutions are scalable, reusable, interpretable where appropriate, and aligned with enterprise architecture and responsible AI principles.

Advanced Analytics, Machine Learning & AI

• Lead development of predictive, prescriptive, optimisation, and forecasting models across multiple business domains.
• Oversee customer segmentation, risk modelling, recommendations, personalisation, propensity modelling, and decision-support solutions.
• Partner with engineering and product teams to operationalise analytical capabilities within production environments and business workflows.
• Support AI initiatives by defining methodologies, evaluation approaches, and performance expectations.
• Promote modern statistical and machine learning techniques while ensuring appropriate application and risk management.

Model Evaluation, Experimentation & Measurement

• Define frameworks to evaluate model performance, business impact, reliability, fairness, and adoption.
• Lead experimentation strategies including A/B testing, causal inference, impact measurement, and test design.
• Collaborate with engineering, product, quality, and business teams on model monitoring and continuous improvement.
• Translate analytical outputs into actionable insights and business recommendations.
• Establish reporting, dashboards, and executive-level performance reviews.

Cross-Functional Collaboration

• Partner with enterprise data teams to ensure access to reliable, high-quality data.
• Collaborate with knowledge management, semantic modelling, and data product teams to improve analytical outcomes.
• Work closely with product, operations, technology, and business leaders to identify and prioritise analytical opportunities.
• Support production deployment of models and analytical services in partnership with engineering teams.
• Provide strategic guidance on where advanced analytics and AI can create value, and where alternative approaches may be more appropriate.

Team Leadership & Development

• Build, lead, and mentor a high-performing team of data scientists and analytics professionals.
• Define organisational structure, hiring strategy, capability development, and career progression pathways.
• Establish effective collaboration models across data, engineering, governance, product, and business teams.
• Coach team members on technical excellence, stakeholder engagement, communication, and business impact.
• Foster a culture of innovation, accountability, continuous learning, and responsible AI.

Required Qualifications

Education

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, Operations Research, Public Health, Informatics, or a related field.
• Master’s degree or PhD preferred.

Experience

• 12-18+ years of experience in data science, machine learning, advanced analytics, applied statistics, or related disciplines.
• 5-8+ years leading data science, analytics, or machine learning teams.
• Proven experience delivering analytical solutions that influence business or operational decision-making.
• Experience partnering with engineering, technology, product, and executive stakeholders.
• Strong background in model development, experimentation, monitoring, and production deployment.
• Experience within a regulated industry preferred.

Technical Expertise

• Deep expertise in statistical modelling, machine learning, predictive analytics, optimisation, experimentation, and decision science.
• Proficiency with Python, R, SQL, notebook-based development environments, and modern machine learning frameworks.
• Experience assessing data quality, feature readiness, model performance, bias, drift, interpretability, and operational fit.
• Understanding of model deployment, monitoring, integration, and lifecycle management within production environments.
• Familiarity with AI, Generative AI, large language model evaluation, recommendation systems, forecasting, personalisation, and decision-support methodologies.
• Strong knowledge of privacy, security, governance, and responsible AI practices.

Preferred Qualifications

• Experience leading data science teams within healthcare, life sciences, financial services, or other highly regulated industries.
• Experience supporting AI-enabled products, digital experiences, operational optimisation, workflow automation, or decision-support capabilities.
• Experience building reusable analytical frameworks and platforms that support multiple business functions.
• Experience defining enterprise standards for model evaluation, observability, monitoring, and continuous improvement.
• Familiarity with semantic models, ontologies, knowledge graphs, or enterprise knowledge management frameworks.
• Strong executive communication and stakeholder management skills.

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Lead ML Platform Engineer

New York City, NY – Hybrid (3 days per week onsite)

$200,000 – $220,000 Base Salary+ Bonus + RSU package available

THE COMPANY

We are partnering with a leading consumer technology and financial services organization that operates at global scale and serves hundreds of millions of users. The business leverages advanced data, machine learning, and real-time decisioning systems to deliver highly personalized customer experiences across a broad portfolio of digital products.

This is an exciting opportunity to join a rapidly expanding machine learning engineering team at a pivotal stage of growth. The organization is investing heavily in recommendation systems, real-time personalization, machine learning platforms, and next-generation AI capabilities, offering engineers the opportunity to work with large-scale distributed systems and production-grade ML infrastructure.

RESPONSIBILITIES

• Design, build, and maintain scalable infrastructure supporting machine learning training, deployment, and inference workloads.
• Develop and optimize backend services, microservices, and cloud-native applications that power real-time machine learning systems.
• Own and enhance ML platform capabilities across cloud infrastructure, model serving, monitoring, and operational tooling.
• Partner closely with Data Scientists to productionize machine learning models and support real-time recommendation and personalization use cases.
• Improve CI/CD pipelines, infrastructure-as-code frameworks, observability, reliability, and system scalability.
• Participate in operational ownership, incident response, and support for critical production services.

SKILLS AND EXPERIENCE

Must-Have

• 7+ years of software engineering or machine learning engineering experience.
• Strong backend engineering expertise with experience building distributed systems at scale.
• Proven experience developing Scala-based microservices and production-grade backend applications.
• Deep knowledge of AWS cloud services, including machine learning infrastructure and managed platforms.
• Hands-on experience with Kubernetes, Docker, Terraform, and modern CI/CD practices.
• Strong Python programming skills.
• Track record of owning production systems, reliability, monitoring, and operational excellence.

Nice-to-Have

• Experience with machine learning infrastructure, MLOps, or model-serving platforms.
• Knowledge of recommendation systems, personalization engines, or CTR optimization.
• Experience with Datadog observability and monitoring.
• Background in adtech, fintech, e-commerce, or other high-scale consumer platforms.
• Exposure to real-time machine learning applications and online inference systems.

BENEFITS

• Competitive base salary and annual bonus
• Equity participation through RSUs
• Hybrid working model
• Opportunity to work on cutting-edge AI and machine learning initiatives
• Significant career growth and technical leadership opportunities
• Exposure to large-scale, real-time production systems

HOW TO APPLY

Please register your interest by submitting your CV via the Apply link on this page.

KEY TERMS

Lead Machine Learning Engineer | Machine Learning Engineering | Platform Engineer | ML Infrastructure | Scala | Python | AWS | SageMaker | Kubernetes | Docker | Terraform | CI/CD | Distributed Systems | Recommendation Systems | Real-Time Systems | MLOps | Backend Engineering | Cloud Infrastructure | Platform Engineering | Datadog | Fintech | Personalization | ML Platform | Software Engineering | Hybrid NYC | Technical Leadership

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Senior/Principal Applied AI Engineer
United States, hybrid or remote. Competitive salary plus benefits.
$150,000 to $205,000 + 15% Bonus

This is an opportunity to take ownership of real, production-grade Generative AI solutions in a highly applied environment. You will work on end-to-end AI delivery, from early prototypes through to scalable deployment, with clear visibility of the impact your work has on customers and internal teams.

The Company
They are a well-established organisation operating in a highly regulated, customer-focused industry. Data and AI are central to their strategy, with significant investment in modern platforms and applied AI capabilities. The business values practical innovation, collaboration, and building technology that delivers measurable outcomes at scale.

The Role
You will be a senior, hands-on contributor within an Applied AI team, responsible for turning GenAI concepts into robust solutions. Key responsibilities include:

• Designing, building, and deploying Generative AI applications across client-facing and internal platforms.
• Developing LLM-powered solutions using prompt engineering, vector databases, and Retrieval-Augmented Generation pipelines.
• Building and owning AI chatbots and conversational agents to production standards, including performance, scalability, and compliance.
• Creating AI agents across digital and voice channels to support real-time interactions.
• Delivering proof-of-concept solutions for use cases such as document understanding, summarisation, and knowledge assistants.
• Optimising model usage, prompts, and parameters to balance accuracy, cost, and reliability.
• Collaborating with product, engineering, data, and external partners to align AI solutions with business priorities.

Your Skills and Experience
You will bring strong, practical experience applying Generative AI in commercial settings, including:

• Advanced Python development skills with modern GenAI and machine learning libraries.
• Hands-on experience with large language models, prompt engineering, and LLM evaluation.
• Proven capability building RAG pipelines and working with vector databases.
• Strong SQL skills and experience working with cloud data platforms.
• Experience delivering production-grade conversational AI or chatbot solutions.
• The ability to communicate complex AI concepts clearly to technical and non-technical stakeholders.
• Comfort working in fast-paced, cross-functional environments.

What They Offer

• Competitive salary and comprehensive benefits package.
• The chance to work on high-impact, enterprise-scale AI products.
• Exposure to a wide range of GenAI use cases, including conversational AI and intelligent automation.
• Clear opportunities for technical growth and influence within a growing Data and AI function.
• A collaborative, supportive culture that values continuous improvement and learning.

How to Apply
If you are an Applied AI Engineer looking to build and deploy meaningful Generative AI solutions, apply now to find out more.

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Principal Data Scientist

Remote | Salary up to $220,000 + 15% bonus

This is an opportunity to step into a senior, high-impact Principal Data Scientist role where you will shape the direction of advanced AI and data science initiatives at scale. You will work on commercially meaningful problems, leveraging cutting-edge techniques including generative AI, while influencing both strategy and delivery across a globally recognised platform.

The Company
They are a well-established, innovation-led organisation focused on delivering data-driven products at scale. With a strong investment in AI and advanced analytics, they partner closely across product, engineering, and design to create impactful, user-focused solutions. Their teams are highly collaborative and operate in a modern, fully remote environment that encourages autonomy and technical excellence.

The Role

• Lead the design and implementation of advanced data science and AI solutions aligned to business objectives
• Provide technical leadership across complex projects, setting direction and best practice for modelling and deployment
• Collaborate with cross-functional stakeholders to identify opportunities and define requirements
• Apply generative AI and other advanced methodologies to solve real-world problems
• Translate technical findings into clear, actionable insights for senior stakeholders
• Oversee project timelines and ensure successful delivery across multiple workstreams

Your Skills and Experience

• Strong commercial experience in data science and machine learning, with recognised expertise in a specialist area
• Deep understanding of production-level AI systems and recent exposure to generative AI techniques
• Proven ability to lead complex projects end to end, from concept through to deployment
• Experience working cross-functionally with product, engineering, or business teams
• Clear and collaborative communication style, with the ability to influence senior stakeholders
• Background in a quantitative or technical field such as Data Science, AI, Mathematics, or similar

What They Offer

• Salary up to $220,000 with a 15% performance bonus
• Fully remote working with flexibility and autonomy
• Opportunity to work on high-impact AI initiatives at scale
• Collaborative, forward-thinking technical environment
• Clear scope for progression into broader technical or strategic leadership roles

How to Apply
If you’re interested in exploring this Principal Data Scientist opportunity, apply now for a confidential discussion.

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Staff AI Engineer

(Hands‑on, LLM Platforms, Technical Lead)

Location: New York
Working model: On‑site
Package: $250,000 + Equity + Bonus

The Opportunity

An established, technology‑driven organisation is building a central AI engineering capability to support complex, data‑intensive decision‑making across the business.

This is a high‑impact individual contributor role for a Senior AI Engineer who enjoys operating close to the commercial core. You’ll take ownership of critical AI systems from architecture through to deployment, working within a small, trusted technical group with direct access to senior stakeholders.

The environment suits someone who thrives in low‑bureaucracy, high‑autonomy settings, where AI is expected to deliver real, measurable value, not experiments for experimentation’s sake.

The Role

You will act as the technical lead for advanced AI tooling, owning system design and delivery across a range of internal use cases.

Responsibilities include:

• Designing and building LLM‑based applications, including retrieval‑augmented generation and agent‑style workflows
• Owning end‑to‑end system architecture, performance, and scalability
• Developing AI tools to support research, monitoring, knowledge discovery, and decision support
• Establishing evaluation and quality frameworks to ensure AI outputs meet high reliability standards
• Reviewing code, setting engineering standards, and supporting the development of other engineers
• Partnering closely with non‑technical users to translate complex workflows into intuitive AI products
• Assessing third‑party tooling and platforms where appropriate

This is a deeply hands‑on role with real ownership.

What We’re Looking For

Core requirements:

• Strong software engineering background (Python preferred)
• Proven experience building production AI systems, particularly modern LLM applications
• Solid understanding of:
  • Prompt design and iteration
  • Embedding pipelines and vector databases
  • RAG architectures and tool‑use patterns
  • Model evaluation and monitoring
• Experience deploying AI products used by non‑technical stakeholders
• Comfortable setting technical direction while remaining a builder

Nice to have:

• Exposure to complex analytical or commercial domains
• Experience working in small, senior engineering teams
• Background in cloud‑native environments

Why Join?

• Ownership of mission‑critical AI systems
• Direct visibility of impact, your work will be used day‑to‑day
• Modern AI stack with freedom to make technical decisions
• Long‑term scope to shape and grow the AI engineering function

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Senior AI Engineer, Agentic Systems
Remote (US) $150,000 to $220,000 + Bonus + Equity

This is an opportunity to join an AI-first technology company building sophisticated agentic systems that automate complex business workflows. You’ll play a key role in shaping both customer-facing AI capabilities and the internal engineering practices that enable teams to build faster, smarter, and more effectively.

The Company
They are an innovative software business leveraging advanced AI and autonomous systems to transform how organisations manage complex operational workflows. Their platform combines proprietary intelligence, enterprise data integration, and agent orchestration to deliver highly automated outcomes at scale. With a remote-first culture and a strong engineering focus, they offer an environment where technical expertise has a direct impact on product direction and business growth.

The Role
As a Senior AI Engineer, you will:

• Design and develop agentic workflows, autonomous systems, and AI-powered product features
• Build orchestration frameworks, tool integrations, and multi-step agent capabilities
• Create robust evaluation, monitoring, guardrail, and observability frameworks for production AI systems
• Collaborate with Product teams to translate complex business processes into reliable agent-driven solutions
• Integrate AI workflows with enterprise platforms, data systems, and third-party technologies
• Own the full software development lifecycle from design through deployment and optimisation
• Contribute to architecture decisions and technical strategy across the engineering function
• Champion the effective use of AI-assisted development tools and help establish engineering best practices
• Work closely with a high-performing team to deliver scalable, production-ready solutions

Your Skills & Experience

• Strong commercial software engineering experience with expertise across distributed systems, APIs, and scalable application development
• Proven experience building applications using LLMs, AI agents, orchestration frameworks, or autonomous workflows
• Experience designing and deploying production-grade AI systems with a focus on reliability and performance
• Knowledge of agent tooling, tool use frameworks, MCP, or similar integration approaches
• Ability to work across the full development lifecycle and take ownership of complex technical initiatives
• Strong communication skills and experience collaborating within remote or distributed teams
• Curiosity about emerging AI technologies and a passion for applying them to solve real-world challenges

Desirable experience includes:

• Exposure to marketing technology, advertising technology, media platforms, or customer data ecosystems
• Experience integrating with enterprise data platforms, cloud data warehouses, or third-party APIs
• Familiarity with LangChain or similar agent orchestration frameworks
• Experience evaluating or running local and self-hosted LLM environments

What They Offer

• Competitive base salary
• Equity participation
• Comprehensive benefits package
• Fully remote working across the US
• Access to collaborative office space for those who prefer a hybrid environment
• The opportunity to influence product strategy and engineering standards
• Exposure to cutting-edge AI and agentic system development
• Clear opportunities for professional growth within a rapidly evolving technology environment

How to Apply
If you’re excited by the future of agentic software engineering and want to build AI systems that have a tangible impact, apply today to learn more about this opportunity.

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STAFF AI ENGINEER

Palo Alto, California, United States (On-site / Hybrid)

The Role

We’re hiring a Staff AI Engineer to build and scale production-grade GenAI systems powering enterprise AI applications.

This is a high-ownership IC role focused on LLM systems, agent frameworks, and production AI infrastructure. You’ll take foundation models and turn them into scalable, reliable systems used for copilots, automation, and internal workflows.

You’ll work across architecture and implementation in a fast-moving environment with rapid production iteration.

What You’ll Build

• Production LLM-powered services and applications
• Enterprise copilots and conversational AI systems
• Text-to-code and natural language SQL systems
• Agent frameworks and tool-using AI systems
• Workflow automation powered by foundation models
• API layers for LLM integration across systems
• Scalable GenAI infrastructure and deployments
• CI/CD pipelines for AI services

What You Bring

• 8-12+ years software or ML engineering experience
• Strong experience building production LLM or ML systems
• Deep understanding of foundation models and LLM APIs
• Strong backend and distributed systems experience
• Experience with AWS production environments
• Kubernetes / containerized deployment experience
• Strong systems thinking (latency, scaling, reliability trade-offs)

Strong Preference For

• ML engineering background over traditional full-stack
• Experience building GenAI or agentic systems in production
• Strong analytical background (PhD-level NLP/CV a plus)

Why This Role

• Build and scale core GenAI infrastructure with real impact
• High ownership from architecture through production
• Fast iteration cycles and strong technical autonomy
• High visibility with senior technical leadership
• Opportunity to shape foundational AI systems at scale

• Opportunity to shape foundational AI systems at scale

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Senior Machine Learning Scientist – REMOTE

This is an opportunity to join a high-growth AI SaaS business using NLP and GenAI to transform unstructured customer feedback into actionable business insights. You’ll work at the intersection of Machine Learning research and production, developing models that directly influence customer experience and commercial outcomes.

The Company
They are an AI-focused technology company helping organisations unlock value from large-scale customer feedback data. With strong growth, expanding enterprise clients, and significant investment in AI, they are building innovative NLP and LLM-powered products that drive measurable business impact.

The Role
You will develop and deploy advanced NLP and GenAI solutions across the full ML lifecycle.
Key responsibilities:

• Build and improve models for information extraction, retrieval, re-ranking, and sentiment analysis.
• Fine-tune language models and optimise LLM performance.
• Design and evaluate experiments to improve product outcomes.
• Develop production-ready machine learning solutions.
• Work with agentic AI systems and modern NLP architectures.
• Collaborate closely with Product, Engineering, and senior stakeholders.

Your Skills & Experience

• Strong commercial experience in Machine Learning and NLP.
• Hands-on experience fine-tuning language models and working with LLMs.
• Knowledge of GenAI and agentic AI patterns.
• Experience working with large, complex datasets.
• Understanding of model deployment and productionisation.
• Strong communication and stakeholder management skills.
• A practical approach to solving real-world business problems.

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Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

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Senior Fullstack Engineer

$150,000-$180,000

4 days/month on site in Houston

A fast-growing organisation is seeking an experienced Full Stack AI Engineer to design, develop, and deploy production-grade applications that combine modern software engineering with practical AI capabilities. This role is ideal for a software engineer who has evolved into AI-focused development and has hands-on experience integrating large language models, generative AI solutions, retrieval systems, and intelligent workflows into enterprise applications.

The successful candidate will own solutions across the full technology stack, from user interfaces and APIs to data pipelines and AI-enabled features. You’ll work closely with product, data, and engineering stakeholders to deliver scalable, business-focused solutions in a collaborative environment.

Key Responsibilities
Solution Design & Architecture

• Design and implement end-to-end applications spanning frontend, backend, data, and AI layers.
• Contribute to architecture decisions, technical reviews, and engineering standards.
• Develop scalable, secure, and maintainable systems suitable for enterprise environments.
• Create patterns and frameworks for AI-enabled application development.

Full Stack Development

• Build user-facing web applications, APIs, workflows, and data-driven solutions.
• Translate analytical and AI outputs into intuitive user experiences.
• Develop applications using modern frontend frameworks and Python-based backend technologies.
• Deliver responsive dashboards, data applications, and self-service tools that support business users.

AI & Intelligent Systems

• Implement AI-powered features such as conversational interfaces, semantic search, document processing, and workflow automation.
• Integrate LLMs, retrieval-augmented generation (RAG), agent-based systems, and AI services into production applications.
• Evaluate and select appropriate AI tools, frameworks, and platforms.
• Collaborate with data and machine learning teams to operationalise AI capabilities.

Data & Platform Integration

• Build and maintain data ingestion pipelines and integration workflows.
• Connect applications to data platforms, model endpoints, and enterprise data sources.
• Ensure data quality, reliability, scalability, and performance.
• Support AI memory systems, knowledge retrieval mechanisms, and data synchronisation processes.

Engineering Excellence

• Leverage AI-assisted development tools as part of daily engineering workflows.
• Implement CI/CD pipelines, automated testing, monitoring, and observability practices.
• Participate in code reviews and contribute to engineering best practices.
• Maintain high standards for security, documentation, testing, and software quality.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
• 8+ years of professional software engineering experience.
• Minimum 5+ years of hands-on full stack development experience.
• Recent experience applying AI technologies within software products, including at least 2+ years working with practical AI implementations.
• Strong understanding of:
• Large Language Models (LLMs)
• Generative AI applications
• Agentic systems and AI workflows
• Retrieval-Augmented Generation (RAG)

• Experience building RESTful APIs and backend services.
• Strong frontend development experience using frameworks such as React, Angular, or similar technologies.
• Strong backend development experience using Python frameworks such as FastAPI, Flask, or Django.
• Experience working with cloud-native applications, with a preference for Google Cloud Platform (GCP).
• Experience with data-intensive applications and platform integrations.
• Hands-on use of AI-assisted coding tools within the software development lifecycle.
• Strong communication, collaboration, and stakeholder engagement skills.
• Experience operating in fast-paced environments with evolving requirements.

Preferred Qualifications

• Experience integrating LLMs, RAG frameworks, AI APIs, and intelligent agents into production environments.
• Experience with modern data platforms, lakehouse architectures, or large-scale data ecosystems.
• Background working in startup, scale-up, or small-to-mid-sized engineering teams.
• Experience with infrastructure-as-code, CI/CD automation, and cloud deployment practices.
• Familiarity with agile software delivery methodologies.
• Experience owning products and systems throughout their full lifecycle.
• Strong product mindset with a focus on usability and business impact.

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AI/ML Engineer

Amsterdam (3 days per week in office) | €75,000 including holiday allowance
This is an opportunity to join a forward-thinking organisation investing heavily in AI and machine learning to deliver real business impact. You’ll play a key role in taking AI solutions from concept through to production, working on cutting-edge technologies and helping shape the future of AI-enabled products.

The Company
They are a well-established organisation with a strong focus on digital innovation and technology-driven transformation. AI and data are central to their strategy, with a growing portfolio of customer-facing and internal AI solutions. The business offers a collaborative environment where engineers can work closely with product, data, and technology teams to deliver measurable value. They are committed to building scalable, secure, and production-ready AI capabilities across the organisation.

The Role
You will:

• Design, build, and scale AI-powered solutions that deliver measurable business value.
• Develop and maintain Python-based backend services and APIs for AI-enabled products.
• Build and optimise AI assistant workflows using modern orchestration frameworks and LLM technologies.
• Translate business requirements into production-ready AI services and applications.
• Collaborate with data teams to access, transform, and leverage enterprise data effectively.
• Integrate AI capabilities into broader digital products and business workflows.
• Create reusable tools, services, and engineering patterns to accelerate future AI initiatives.
• Implement automated testing and quality assurance practices for AI solutions.
• Contribute to CI/CD processes, containerised deployments, and operational readiness.
• Ensure security, privacy, and responsible AI standards are embedded throughout the development lifecycle.

Your Skills & Experience

• Strong commercial experience developing production-grade applications in Python.
• Experience building APIs, backend services, and scalable software solutions.
• Hands-on experience with LLMs, AI assistants, and agent-based workflows.
• Knowledge of tools such as FastAPI, Pydantic, LangChain, LangGraph, and OpenAI APIs.
• Experience working with SQL, data pipelines, and modern data platforms.
• Understanding of automated testing frameworks and AI evaluation approaches.
• Familiarity with Docker, CI/CD pipelines, cloud environments, and DevOps practices.
• Strong stakeholder communication skills and the ability to work across multidisciplinary teams.
• Passion for building reliable, maintainable, and impactful AI products.

What They Offer

• Salary of €75,000 including holiday allowance.
• Hybrid working model with 3 days per week in the Amsterdam office.
• Opportunity to work on high-impact AI and machine learning initiatives.
• Exposure to modern AI tooling, cloud technologies, and large-scale products.
• A collaborative environment with strong opportunities for learning and career progression.
• The chance to influence the direction of AI engineering within a growing capability.

How to Apply
If you’re an AI/ML Engineer looking to build production-ready AI products and work on impactful machine learning solutions, apply today to find out more.

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