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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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Founding AI Engineer

Fort Worth, TX (4 Days Onsite – Non-Negotiable)
Compensation: Up to $300,000 Base + Meaningful Equity

About the Opportunity

We are partnering with a well-capitalized, publicly traded company undergoing a significant AI-driven transformation. The organization operates in a highly data-rich environment and is making a substantial long-term investment in artificial intelligence, software development, automation, and intelligent decision systems.

This is not a research role.

This is an opportunity for a highly capable AI Engineer to build production-grade AI products that solve real business problems, influence strategic decisions, and ultimately become core to the company’s competitive advantage. The successful candidate will work directly with executive leadership and have a meaningful role in shaping the company’s AI roadmap from the ground up.

Why This Role Stands Out

Most AI jobs today focus on prototypes, experimentation, and proof-of-concepts.

This role is different.

You’ll be responsible for building AI systems that are actively used, trusted, and integrated into day-to-day operations. You’ll have the autonomy to identify opportunities, architect solutions, deploy production applications, and see the direct impact of your work across the business.

For engineers who enjoy operating at the intersection of:

• AI Agents
• LLM Infrastructure
• Full-Stack Product Development
• Data Systems
• Model Fine-Tuning
• Automation & Workflow Design

this is a rare opportunity to build something meaningful from an early stage.

What You’ll Be Building

AI Products & Agentic Systems

• Design and deploy AI agents that automate complex workflows.
• Build production-ready LLM applications for internal and external users.
• Develop agent orchestration frameworks and AI-powered decision-support systems.
• Create scalable architectures that move beyond demos into real-world business applications.

Generative AI Infrastructure

• Implement RAG pipelines and vector database architectures.
• Develop evaluation frameworks to measure model performance and reliability.
• Fine-tune and customize models using LoRA and modern adaptation techniques.
• Work with open-source and commercial LLM ecosystems.

Full-Stack Product Development

• Develop backend services and APIs in Python.
• Build user-facing applications using modern frontend frameworks such as React and TypeScript.
• Create intuitive interfaces that make AI useful for technical and non-technical users alike.

Data & Platform Engineering

• Design scalable data architectures and database-backed applications.
• Connect AI systems with operational and business data sources.
• Ensure applications are observable, maintainable, secure, and performant in production environments.

What We’re Looking For

We are interested in builders.

The ideal candidate has experience taking an idea from concept to deployment and can comfortably operate across multiple layers of the stack.

Core Requirements

• Strong professional software engineering experience in Python.
• Experience building production-grade AI applications.
• Hands-on experience with:
  • AI Agents
  • RAG architectures
  • Vector databases
  • LangChain, LangGraph, or similar frameworks
  • LoRA fine-tuning workflows
  • LLM evaluation methodologies
• Experience developing APIs, backend services, and scalable systems.
• Strong understanding of application security and software architecture.
• Demonstrated ability to build software that real users depend on.

Bonus Points

• React and TypeScript expertise.
• Experience serving or self-hosting open-source models.
• Experience with GGUF, Safetensors, or model optimization workflows.
• Background in distributed systems, platform engineering, or MLOps.
• Startup mentality with a bias toward execution and ownership.

Who Thrives Here

This environment is best suited for engineers who:

• Move quickly without sacrificing quality.
• Prefer ownership over bureaucracy.
• Want direct access to business leaders and decision-makers.
• Enjoy turning ambiguity into working products.
• Are excited by the opportunity to build AI systems that become mission-critical to an organization.

You’ll be joining a team that views AI as a strategic advantage-not a side project.

Location Requirement

This role is based in Fort Worth, Texas and requires onsite presence four days per week.

This requirement is non-negotiable. The company believes the strongest outcomes come from close collaboration between engineering, operations, and leadership teams, and has intentionally built an onsite-first culture around innovation and execution.

Compensation

• Base salary up to $300,000
• Meaningful equity participation
• Long-term wealth creation opportunity
• Executive visibility and influence
• Opportunity to help define the future direction of AI within the organization

Confidential Search

This search is being conducted on a confidential basis. Further company details will be shared with qualified candidates during the interview process.

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Head of Platform & Engineering

London (Hybrid, near Tower Hill)

The Company
They are a global research and insights consultancy that partners with leading brands to inform strategic decision making. By combining advanced analytics, technology, and deep market understanding, they help organisations better understand customers and expand into new markets. Their work involves processing billions of data points per project, with a growing focus on synthetic data and AI-led innovation.
You will join a specialist synthetic data team that operates at the intersection of research, machine learning, and platform engineering, building tools that are shaping the future of data-driven insights.

The Role

• Own and define the platform strategy for a large-scale synthetic data and generative AI ecosystem
• Lead and develop a cross-functional engineering team, setting technical standards and best practices
• Build a scalable, secure, and high-performing platform used across global teams
• Bridge the gap between research, machine learning, and engineering to productionise advanced AI models
• Drive adoption of MLOps best practices including CI/CD, model lifecycle management, and reproducibility
• Ensure enterprise-grade governance, security, and privacy standards are embedded in the platform

Your Skills & Experience

• Strong technical leadership experience across software engineering, data engineering, or machine learning engineering
• Proven experience building and scaling complex data or ML platforms within a product-led environment
• Deep understanding of distributed systems, platform architecture, and high-throughput data processing
• Strong experience with Python and modern data and ML ecosystems
• Hands-on experience with GCP, Kubernetes, and infrastructure as code such as Terraform
• Experience implementing MLOps frameworks and managing model pipelines in production

What They Offer

• Hybrid working with a central London office (near Tower Hill)
• Opportunity to lead a high-impact AI platform from strategy through to delivery
• A collaborative, cross-disciplinary team environment
• Strong scope for leadership growth and influence across the business

How to Apply
If you are interested in this Head of Platform & Engineering role, please apply with your CV for consideration.

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AI Automation Lead

London (3 Days a week)

The Company
They are a well-established investment-focused organisation with a strong track record of managing sophisticated portfolios. The business fosters a collaborative and forward-thinking culture, where technology and data are central to operational excellence. With a focus on innovation and continuous improvement, they are investing heavily in modern data and AI capabilities to drive impact across core functions. The environment encourages ownership, creativity, and cross-functional collaboration.
The Role

• Design and deliver a fully automated, end-to-end reporting platform
• Build intelligent workflows to automate data ingestion, validation, and reconciliation processes
• Develop scalable systems that replace manual operational tasks with robust, observable solutions
• Implement exception handling and human-in-the-loop mechanisms where needed
• Ensure systems are accurate, auditable, and resilient in a production environment
• Collaborate closely with cross-functional stakeholders to translate operational requirements into technical solutions

Your Skills and Experience

• Strong commercial experience in applied AI or automation engineering within operational environments
• Strong programming skills in Python and SQL
• Experience building data pipelines and integrating systems via APIs and structured data feeds
• Proven ability to build reliable, production-grade systems with monitoring and testing in place
• Experience with version control and CI/CD practices
• Strong system design capability with an end-to-end mindset

What They Offer

• Competitive salary and comprehensive benefits package
• Opportunity to build a high-impact AI platform from inception
• A collaborative and inclusive working culture
• Strong exposure to modern AI, data engineering, and automation technologies
• Clear scope for professional growth and ownership of key systems

How to Apply
If you are interested in applying for this Applied AI Engineer role, please submit your CV for consideration.

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AI Engineering Lead
Remote (UK-based, with occasional travel)

This is a rare opportunity to take ownership of AI strategy and delivery within a fast-scaling, international business. You will shape how artificial intelligence is applied across multiple industries, working directly with senior leadership to turn innovation into measurable commercial impact.

The Role

• Define and deliver the AI strategy across a diverse group of businesses
• Design scalable architecture and build production-ready AI systems
• Identify and prioritise high-impact use cases that drive efficiency and commercial value
• Evaluate and implement tools, platforms, and frameworks for AI deployment
• Work closely with senior stakeholders, including C-level leadership, to align AI initiatives with business goals
• Establish best practices for AI engineering, deployment, and governance
• Support adoption across decentralised teams while enabling local autonomy
• Act as the senior technical lead for AI, shaping future capability and direction

Your Skills & Experience

• Strong commercial experience building and deploying AI-powered applications
• Hands-on expertise with Python and modern AI tooling, including large language models
• Experience designing and implementing scalable technical architectures
• Understanding of prompt design, retrieval-based systems, and orchestration frameworks
• Experience integrating AI solutions into business systems and workflows
• Comfortable working across both technical and non-technical stakeholders
• Ability to operate autonomously in a fast-moving, evolving environment

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Senior AI/ML Engineer – Foundation Models & Agentic AI
Life Sciences AI | Biotech / Therapeutics / Computational Biology

What You’ll Work On

• Develop and train proprietary foundation models on multi-omics data (genomics, transcriptomics, proteomics, metabolomics)
• Design novel algorithms to integrate and differentiate across omics modalities
• Own the full training pipeline: data ingestion, tokenization, pretraining, and evaluation
• Push the state of the art – we are building models that do not exist yet

Agentic AI for Life Sciences

• Build and deploy AI agents that assist researchers across therapeutic development, computational chemistry, and biology
• Design multi-agent architectures using LangChain, LangGraph, and custom orchestration layers
• Integrate agents with internal databases, experimental systems, and third-party scientific tools
• Develop agentic workflows for use cases in cosmetics R&D, drug discovery, and clinical analysis

Production ML Infrastructure

• Own model deployment, scaling, and serving infrastructure
• Optimize inference using NVIDIA TensorRT-LLM, Dynamo, Triton, and related tooling
• Partner with software engineering on integration into our broader platform
• Maintain reliability, performance, and observability across deployed models

What We’re Looking For

Required

• Strong hands-on ML/AI engineering experience – you write real code, not just direct others
• Deep proficiency in Python and PyTorch – this is non-negotiable
• Experience training, fine-tuning, and deploying foundation models from scratch or from pretrained checkpoints
• Familiarity with the Hugging Face ecosystem (Transformers, Datasets, PEFT, Accelerate)
• Experience with LangChain and/or LangGraph for agentic pipeline development
• Working knowledge of the NVIDIA stack: TensorRT-LLM, Triton Inference Server, Dynamo
• Comfort with large-scale distributed training tools: DeepSpeed, xFormers
• Strong understanding of state-of-the-art model architectures (transformers, SSMs, diffusion, etc.)
• Ability to collaborate across technical and non-technical teams – bio, chem, software, clinical
• Excellent communication skills – you can explain a training run to a chemist

Strongly Preferred

• Experience with omics data (any modality: genomic, proteomic, transcriptomic, metabolomic)
• Background in computational biology, computational chemistry, or bioinformatics
• Prior work in biotech, pharma, or life sciences AI (not required but a plus)
• Experience building or contributing to multi-agent systems in a production environment
• Track record of independent research or open-source contributions in ML

Technical Skills Summary

Core ML / Training

• PyTorch – primary framework
• DeepSpeed – distributed training and ZeRO optimization
• xFormers – memory-efficient attention and transformer components
• Hugging Face Transformers, PEFT, Accelerate
• Training and fine-tuning large language and multimodal models

Inference & Deployment

• NVIDIA TensorRT-LLM – high-performance LLM inference
• NVIDIA Dynamo – inference orchestration and scheduling
• Triton Inference Server – model serving and batching
• Model quantization, distillation, and latency optimization

Agentic & Orchestration

• LangChain / LangGraph – agent design and multi-agent orchestration
• Tool-use, RAG pipelines, and memory systems
• API and system integration across scientific data sources

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Staff Software Engineer – AI Platform · Full-Time

About the Role

We’re looking for a Staff Software Engineer to join our AI platform team at a fast-growing, healthcare-focused startup. This is a hands-on technical leadership role – you’ll be the person who dreams up what’s possible, architects the solution, writes the code, and then hands off polished specs

You won’t be managing people. You’ll be doing the work: designing agentic AI workflows, building generative AI features, and thinking creatively about what could make our platform genuinely better for the people using it. If you’ve ever been the person in the room who says “what if we just built it this way” and then goes home and actually builds it – this role is for you.

What You’ll Do

• Design, architect, and implement agentic AI and generative AI workflows that power core platform capabilities
• Take ownership from idea to implementation – whiteboard it, validate it, ship it
• Identify creative, non-obvious opportunities to leverage AI across the platform and bring those ideas to life
• Contribute to marketing technology initiatives and help build commercially viable AI models

What We’re Looking For

• Proven experience building agentic AI systems or AI-powered chatbots from scratch – not just integrating APIs, but architecting the underlying system
• Strong Python skills across relevant frameworks – Django, Flask, and/or FastAPI
• Comfort with the full development lifecycle: design, implementation, testing, validation, and iteration
• Experience building and deploying on AWS
• Ability to code without relying on AI-assisted tooling – you understand what you’re writing and why
• A builder mentality – you move fast, think creatively, and take pride in shipping things that work
• Frontend experience with React is a plus, though backend depth is what matters most here

Nice to Have

• Experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar agentic frameworks
• Background in healthcare, health tech, or a similarly regulated industry
• Experience working with distributed or cross-timezone engineering teams

Why This Role

• Greenfield AI work – you’ll have real influence over what gets built and how
• Collaborate with a tight-knit, high-trust international team
• Meaningful domain – the work you do will have a direct impact on how healthcare is delivered
• Salary range up to 350k for the right level

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Lead AI Engineer

London (Hybrid, 1 to 2 days per week)

The Company
They are a leading UK consumer-focused financial services business with a broad product portfolio and millions of customers. Operating at scale, they are investing heavily in AI to enhance customer experience, drive efficiency, and strengthen risk and fraud capabilities. A new generative AI team is being built to sit within a broader AI and MLOps function, moving from contractor-led delivery to a permanent, strategically aligned capability. This is a high-visibility area with strong internal demand and clear executive backing.

The Role
You will lead the design and delivery of AI solutions that directly impact core operations and customer journeys.

• Own end-to-end delivery of AI systems, from problem definition through to production
• Design and deploy LLM and RAG-based solutions, including chat assistants for customer support and contact centre optimisation
• Drive automation across complaints handling, triage, fraud detection, and customer data workflows
• Define architecture and make decisions around build versus buy solutions
• Work closely with engineering, product, and risk teams to ensure compliant and scalable solutions
• Implement robust MLOps practices including monitoring, evaluation, and system reliability

Your Skills & Experience

• Strong commercial experience delivering production-grade AI systems end to end
• Deep expertise in generative AI, including LLMs, RAG, and agent-based systems
• Solid software engineering background with experience in scalable system design and APIs
• Hands-on experience with MLOps, including deployment, monitoring, and lifecycle management
• Proven ability to lead multiple AI initiatives and deliver measurable business outcomes
• Experience working in large, complex organisations with high data volumes

What They Offer

• Competitive pension and benefits package
• Hybrid working with flexibility
• Opportunity to shape a new AI capability within a large organisation
• Clear progression as the AI function scales

How to Apply
If you are interested in leading AI innovation in a high-impact, enterprise environment, apply now to find out more.

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Title: AI Engineer

Location: Remote, United States

Compensation: Up to $250,000 + Equity

We’re partnered with a mission-driven healthcare technology company working at the intersection of clinical data and AI. They’re reimagining how complex clinical workflows are automated, with a focus on making high-quality healthcare data more accessible, structured, and actionable. This is a company building something genuinely novel in a space where the stakes are high and the impact is real.

This is a high-impact role where you will lead AI innovation from the ground up. You won’t just be implementing models, you’ll own the full lifecycle of production AI systems, define how clinical data is extracted and structured at scale, and influence the company’s long-term AI direction. The work spans LLMs, computer vision, and mixed-modal approaches in a domain where rigor and accuracy are non-negotiable.

What You’ll Do

• Design, develop, and deploy novel AI/ML systems – with a focus on LLMs and computer vision – to recover, extract, and automate clinical data tasks across diverse data types including medical records, imaging, and clinical reports
• Build robust prototypes and transition them to scalable, near-production-ready code, applying strong software engineering fundamentals throughout
• Design and execute rigorous statistical validation and evaluation frameworks, defining performance metrics and ensuring models meet stakeholder-defined accuracy thresholds
• Own the human-in-the-loop (HITL) lifecycle, ensuring deployed models can continuously improve over time through structured feedback capture
• Partner closely with software engineering to bring proof-of-concept solutions into production, contributing to key architectural decisions along the way
• Proactively identify high-impact AI opportunities across the business and define how advanced capabilities can address them
• Champion best practices for documentation, experimentation, and code quality across the model development lifecycle – and potentially mentor others in doing the same
• Actively evaluate state-of-the-art approaches, bringing innovative ideas and methods to the team
• Apply and uphold healthcare data privacy regulations and ethical standards in all AI development work

Requirements

• MSc or PhD in computer science, engineering, applied mathematics, statistics, or a related field; BSc with equivalent demonstrated experience also considered
• 2-5+ years of relevant experience in AI/ML engineering or data science, with increasing scope and responsibility over time
• Deep hands-on Python expertise; polyglot coder comfortable across modern programming languages
• Significant experience with at least one deep learning framework (PyTorch, TensorFlow, etc.) applied to LLMs or computer vision in production contexts
• Proven knowledge of the healthcare data domain in at least one area: EHR/EMR, clinical imaging, clinical workflows, or clinical research
• Extensive experience with modern cloud compute and storage platforms (AWS, Azure, Databricks, Snowflake, etc.)
• Solid understanding of database technologies (SQL, NoSQL, etc.)
• Strong familiarity with SDLC and agile methodologies
• Ability to independently architect end-to-end solutions and clearly communicate how they deliver business value
• Excellent written and verbal communication skills – including the ability to present complex technical concepts to non-technical stakeholders

Nice to Have

• Experience with computer vision or multimodal model development
• Background in clinical research, regulated healthcare environments, or medical data pipelines
• Familiarity with EDC systems or clinical trial data infrastructure
• Experience designing or improving HITL feedback systems in production
• Exposure to AI evaluation frameworks or quality assessment tooling

If you’re interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

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