Senior AI Engineer
Forward Deployed AI, Enterprise AI Unit. Cambridge, UK
Competitive salary and benefits
Are you ready to turn ambiguous enterprise challenges into credible, production AI that moves the needle for patients and the business? Do you want to ship agentic and retrieval-augmented systems that colleagues rely on every day? Join our forward-deployed AI engineering team within a newly created enterprise unit in Cambridge, where your work will help accelerate how we discover, develop and deliver medicines.
You will be part of a hands-on group that builds with AI and ships AI. We convert scattered data and unstructured knowledge into dependable systems with measurable outcomes. In this role, you will design and deliver end-to-end solutions, lead the rigor that makes demos production-grade, and partner closely with authorities across the company to bring the latest techniques into real-world use.
Based in Cambridge with a competitive salary and benefits, you will have the autonomy to craft solutions from prototype to deployed service, backed by strong platforms, clear sponsorship and a culture that values both ambition and disciplined engineering.
Accountabilities:
Agentic AI Development: Design, implement and iterate agentic workflows that orchestrate tools, sub-agents and multi-step reasoning to deliver deterministic, auditable outcomes to business users.
Retrieval-Augmented Systems: Build robust RAG pipelines and context engineering strategies that ground LLM outputs in enterprise knowledge, improve factuality and reduce hallucinations.
Evaluation and Quality: Establish ground-truth datasets, LLM-as-judge and rule-based evals, and regression suites that separate signal from prompt noise and ensure consistent performance over time.
Production Software Engineering: Translate prototypes into reliable services with structured outputs, clear interfaces, packaging, testing and traceability that meet critical software standards.
Platform Integration and Observability: Integrate with Kubernetes and cloud platforms, implement CI/CD, and instrument systems for cost, latency, caching and evaluation dashboards to sustain performance at scale.
Partner Teamwork: Work with subject-matter experts and product owners to turn ambiguous problems into clear specifications, communicate trade-offs, and land solutions that create business value.
Secure and Scalable Deployment: Apply gateway-based inference patterns and led LLM platforms where appropriate to balance security, performance and maintainability.
Continuous Innovation: Scan the evolving AI landscape, assess when fine-tuning or distillation is warranted, and proactively upgrade techniques to keep solutions robust and competitive.
Essential Skills/Experience:
Advanced University degree in mathematics, computer science or another relevant numerical/computational subject area; alternatively, equivalent experience in relevant research or industry. PhD or equivalent experience desirable.
Deep and validated AI foundations — ability to go deep into the maths and nuances of neural networks, transformers, statistics, evaluation methodology — applied with judgement
Hands-on experience designing and shipping production-grade systems built around LLMs: agentic workflows, RAG, tool use, structured outputs and multi-step orchestration
Practical experience with modern agent-integration patterns — MCP, tool/skill ecosystems, agent-to-agent communication, sub-agents and context engineering — and judgement about when to use each
Demonstrated ability to deliver production-grade software using AI coding assistants with the subject area that critical software demands — specs, tests, evals, code review, traceability — not just ad-hoc prototyping
Excellent evaluation skills: designing ground-truth datasets, building LLM-as-judge and rule-based evals, regression suites, calibration and statistical reasoning to distinguish signal from prompt noise
Strong Python — structured-output validation, packaging — and focused testing practice; confident scaffolding a service from prototype to deployed
Excellent problem-solving, collaboration and communication skills; able to translate ambiguous business problems into specs, collaborate with SMEs, and present results to senior stakeholders
Experience with Kubernetes and cloud platforms (Azure and/or AWS), CI/CD, and LLM observability (cost, latency, caching, eval dashboards)
Desirable Skills/Experience:
Experience training, fine-tuning or distilling models when the problem genuinely calls for it
Familiarity with managed-LLM platforms (e.g. AWS Bedrock, Azure OpenAI) and gateway-based inference patterns. End-to-end software life cycle and experience shipping and deploying production code.
Full-stack delivery experience — comfortable leading a thin frontend when needed; this is not a frontend role and professional UI skills are not required
Interest in working on real-world enterprise problems in a research-driven organisation; pharma or life-sciences experience welcomed but not required
When we put unexpected teams in the same room, we ignite bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
Why AstraZeneca:
Here, technology and science meet to change what’s possible for patients. You will join a company investing boldly in digital and data to become truly data-led, where unexpected teams come together to address problems that have never been solved before. We empower engineers to experiment through hackathons and real-world pilots, build at enterprise scale with modern platforms, and learn continuously in a supportive, high-standards culture that values kindness alongside ambition. Your contribution will unlock the potential of our science, streamline how we work, and help bring medicines to people faster.
Step into this role to design and ship AI systems that matter—bring your expertise to Cambridge and help turn pioneering ideas into real-world impact today!
Date Posted
28-May-2026Closing Date
11-Jun-2026Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.