AI Lead Engineer in Bristol

Newpage Solutions is a global digital health innovation company helping people live longer, healthier lives. We partner with life sciences organizations—including pharmaceutical, biotech, and healthcare leaders—to build transformative AI and data driven technologies addressing real-world health challenges.

We’re seeking a highly experienced, technically exceptional Lead AI Engineer to architect and deliver next-generation Generative AI and Agentic systems. You will drive end-to-end innovation—from model selection and orchestration design to scalable backend implementation—while collaborating with cross-functional teams to transform AI research into production-ready solutions. You will define the standards for quality, scalability, and innovation across all AI initiatives.

Develop AI Applications & Agentic Systems

• Architect, build, and optimize production-grade Generative AI applications using orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, n8n, Pydantic AI or custom orchestration layers integrating with LLMs such as GPT, Claude, Gemini as well as self-hosted LLMs along with MCP integrations.
• Agentic AI frameworks (Agno, AutoGen, CrewAI etc.)
• Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone / ChromaDB / Weaviate / pgvector / etc), search engines such as ElasticSearch / Solr using both TF/IDF BM25 based full text search as well as similarity search techniques.
• Microservices and modular backends using Python or Javascript or Java aligned with domain driven design, SOLID principles, OOP, and clean architecture.
• Databases including relational (PostgreSQL, MySQL), document (MongoDB, DocumentDB), Key-Value (Redis / DynamoDB), Graph (neo4j, Neptune, Janus Graph).
• Cloud native deployments in hyper-scalers such as AWS / GCP / Azure using containerization and orchestration with Docker / Kubernetes or serverless architecture.
• Multi-modal workflows using text, image, voice and video.
• TDD, well-structured and clean code with linting, domain driven design, security-first design (secrets management, rotation, SAST, DAST), comprehensive observability (structured logging, metrics, tracing), containerization & orchestration (Docker, Kubernetes), automated CI/CD pipelines (Ex: Github Actions, Jenkins).
• Design robust prompt & context engineering frameworks to improve accuracy, repeatability, quality, cost, latency.

AI Assisted Development, Context Engineering & Innovation

• Use AI-assisted development tools such as Claude Code, GitHub Copilot, Codex, Roo Code, Cursor to accelerate development while maintaining code quality and maintainability.
• Utilise coding assistant tools with native instructions, templates, guides, workflows, sub-agents and more to create developer workflows to improve development velocity, standardisation, reliability across AI teams.
• Partner with Product, Design, and ML teams to translate conceptual AI features into scalable user-facing products.
• Provide technical mentorship and guide team members in system design, architecture reviews, and AI best practices.
• Lead POCs, internal research experiments, and innovation sprints to explore and validate emerging AI techniques.

Qualifications

• 7–12 years of total experience in software development, with at least 3 years in AI/ML systems engineering or Generative AI.
• Experience with cloud native deployments and services in AWS / GCP / Azure with the ability to architect distributed systems.
• A no-compromise attitude with engineering best practices such as clean code, TDD, containerization, security, CI/CD, scalability, performance and cost optimization.
• Active user of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) with demonstrable experience using structured workflows and sub-agents.
• Python or Javascript experience with strong grasp of OOP, SOLID principles, 12-factor application development and scalable microservice architecture.
• Proven track record developing and deploying GenAI/LLM-based systems in production.
• End-to-end implementation experience using vector databases and retrieval pipelines.
• Experience with GitHub Actions, Docker, Kubernetes, and cloud-native deployments.
• Obsessed with clean code, system scalability, and performance optimization.
• Can balance rapid prototyping with long-term maintainability.
• Excel at working independently while collaborating effectively across teams.
• Stay ahead of the curve on new AI models, frameworks, and best practices.
• Bachelor’s or Master’s in Computer Science, Machine Learning, or a related technical discipline.

Bonus Skills / Experience

• Understanding of MLOps, model serving, scaling, and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker).
• Experience building streaming + batch data ingestion and transformation pipelines (Spark / Airflow / Beam).
• Mobile and front-end web application development experience.

At Newpage, we’re building a company that works smart and grows with agility—where driven individuals come together to do work that matters. Room to grow – Opportunities for learning, leadership, and career development, shaped around you. Meaningful rewards – Competitive compensation that recognizes both contribution and potential.