AI Engineer

Role

We are hiring an AI Engineer to design, build and optimise production-grade Generative AI and agentic systems for healthcare use cases. This individual-contributor leadership role drives end-to-end innovation from model selection and orchestration to scalable backend implementation and deployment.

Key Responsibilities

• Architect, build and optimise generative AI and agentic applications using frameworks such as LangChain, LangGraph, LlamaIndex and Semantic Kernel.
• Implement Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases (Pinecone, ChromaDB, Weaviate, pgvector).
• Implement guardrails, observability, fine-tuning and model training for domain-specific use cases.
• Build multi-modal workflows handling text, image, voice and video and design robust prompt/context engineering frameworks.
• Develop microservices and modular backends using Python, JavaScript or Java following DDD, SOLID and clean architecture principles.
• Work with various databases (relational, document, key-value, graph) and event-driven systems (Kafka/MSK, SQS).
• Deploy cloud-native solutions on AWS/GCP/Azure using Docker, Kubernetes or serverless architectures.
• Use AI-assisted development tools (Claude Code, GitHub Copilot, Codex, Roo Code, Cursor) to accelerate development while maintaining code quality.
• Run POCs, internal research experiments and innovation sprints to validate emerging AI techniques.

Requirements

• 2–5 years total software development experience, with at least 2 years in AI/ML systems engineering or Generative AI.
• Hands-on experience deploying GenAI/LLM-based systems in production and end-to-end retrieval pipelines using vector databases.
• Practical experience with Python or JavaScript (Java also acceptable) and strong understanding of OOP, SOLID, 12‑factor apps, microservices and scalable architecture.
• Deep knowledge of LLMs, context engineering, prompt construction, optimisation, evaluation techniques, and cost/latency trade-offs.
• Familiarity with cloud platforms (AWS/GCP/Azure), containerisation (Docker), orchestration (Kubernetes) or serverless approaches.
• Active user of AI-assisted development tools and structured workflows for code quality and maintainability.
• Degree in Computer Science, Machine Learning or related technical discipline preferred.

Benefits

• Hybrid working arrangement and full-time employment
• Supportive, people-first culture with open communication
• Emphasis on work–life balance
• Learning, leadership and career development opportunities
• Competitive compensation and meaningful rewards

Location & Type

Bristol (hybrid). Full-time role.