Principal Applied AI Engineer

Location of role Abingdon, UK

Department Information Technology

Key Responsibilities Main Purpose of Job

The Principal Applied AI Engineer is a senior individual contributor responsible for turning high-value scientific and business problems into production AI solutions. Working directly with domain teams, the role discovers and frames problems, understands existing workflows and constraints, prototypes solutions with users, and then engineers, deploys, supports, and improves those solutions in production. This is a hands-on engineering role reporting to the Senior Director, AI Portfolio & Governance, and does not currently have direct reports.

The role operates at the intersection of software engineering, applied AI, and business transformation. It is expected to work through ambiguity, challenge requirements constructively, and remain accountable beyond the prototype until a solution is reliable, adopted, and delivering measurable value.

Principal Applied AI Engineers build on Immunocore's AWS-based agentic AI environment, including Amazon Bedrock / AgentCore and related services. Platform ownership is shared across the AI engineering team: each engineer is expected to understand, maintain, troubleshoot, and safely extend the configured environment, while working with Infrastructure, Security, Data, and enterprise systems teams rather than duplicating their responsibilities.

Key Responsibilities

• Embed with scientific, clinical, regulatory, commercial, and corporate teams to understand current workflows, identify high-value opportunities, and translate ambiguous needs into well-scoped AI solutions.
• Own solutions end-to-end: discovery, workflow design, technical architecture, rapid prototyping, user iteration, engineering, evaluation, deployment, adoption, production support, and continuous improvement.
• Design and build production LLM and agentic applications using approaches such as retrieval-augmented generation (RAG), tool calling, workflow orchestration, structured outputs, and human-in-the-loop controls.
• Build integrations with enterprise systems, APIs, and data platforms, including Snowflake, using narrow, approved access patterns and sound software engineering practices.
• Define and implement evaluation and reliability approaches for non-deterministic systems, including test datasets, automated evaluations, regression testing, observability, logging, versioning, and production monitoring.
• Implement approval gates, human oversight, traceability, and validation evidence appropriate to the risk and regulatory context of each use case, working with IT Compliance, Quality, Legal, Privacy, and Security as required.
• Maintain and evolve Immunocore's AWS agentic AI environment as configured, including Amazon Bedrock / AgentCore and supporting services such as IAM, Lambda, Step Functions, EventBridge, and CloudWatch, in partnership with Infrastructure.
• Contribute to CI/CD, infrastructure-as-code, environment promotion, technical runbooks, production support, resilience, and cost management for the AI environment and deployed solutions.
• Create reusable agent templates, integration patterns, evaluation frameworks, and shared components so successful approaches can be reused across functions rather than becoming one-off solutions.
• Act as a technical counterpart to implementation partners and vendors: review designs and deliverables, challenge technical choices where appropriate, and ensure knowledge and capability are transferred internally.
• Work directly with users after deployment to diagnose issues, improve usability and reliability, measure adoption and outcomes, and iterate quickly based on real-world feedback.
• Stay current on agentic frameworks, model capabilities, AWS AI services, and emerging engineering practices; advise the Head of AI on architecture, build/buy, and technical standards.

Education, Experience and Knowledge

Essential Qualifications

• Degree in computer science, engineering, or a related field, or equivalent practical experience.
• Typically 7+ years of software, cloud, data, or platform engineering experience, including recent hands-on delivery of production LLM applications such as RAG, tool-using agents, workflow automation, and evaluation systems.
• Strong proficiency in Python or a comparable language, with sound software engineering discipline including APIs, testing, source control, and production debugging.
• Strong AWS experience and practical understanding of cloud architecture, IAM, serverless services, observability, infrastructure-as-code, and CI/CD.
• Demonstrated ability to take an ambiguous business or scientific problem from discovery through a working production solution rather than only implementing predefined requirements.
• Strong communication skills and the ability to work directly with non-technical domain experts, explain technical trade-offs clearly, and iterate rapidly with users.

Preferred Qualifications

• Hands-on experience with Amazon Bedrock / AgentCore or comparable enterprise agent platforms and orchestration frameworks.
• Experience delivering AI or software solutions in life sciences, healthcare, GxP, or another regulated environment.
• Experience with enterprise data and application integration, including APIs, event-driven patterns, Snowflake, or similar data platforms.
• Experience with LLM evaluation, observability, guardrails, security controls, and testing of non-deterministic systems.
• Experience working with or taking technical handover from system integrators, consultancies, or software vendors.

Experience & Knowledge

• Product-minded and outcome-oriented: comfortable moving between user discovery, architecture, coding, deployment, and production troubleshooting.
• Security-minded and pragmatic, with least-privilege instincts for agent tools, credentials, data access, and enterprise integrations.
• Comfortable working across existing Infrastructure, Security, Data, Compliance, and enterprise systems teams while personally owning the AI-specific engineering work.
• Able to balance speed with reliability and governance, selecting the level of control, testing, and validation appropriate to the use case.
• Curious, self-directed, and comfortable learning unfamiliar scientific or business workflows quickly enough to build useful solutions with domain experts.

About the Company Immunocore (NASDAQ: IMCR) is a pioneering, commercial-stage T cell receptor biotechnology company whose purpose is to develop and commercialize a new generation of transformative medicines which address unmet patient needs in oncology, infectious diseases and autoimmune disease. Our leaders in R&D are internationally recognised as some of the biotech industry’s most successful drug developers. We are creating not just an environment where great minds can interact but an innovation powerhouse answering the big questions.

Focused on delivering first-in-class biological therapies to patients, we have developed a highly innovative soluble TCR platform. Our ImmTAX molecules underpin a new generation of precision engineered drugs that harness the immune system to treat a broad spectrum of diseases with high unmet medical need, including oncology, infectious diseases and autoimmune diseases.

At Immunocore, we recognize that our employees are our greatest asset. We value the unique contributions each person brings to our team. By embracing Science, Trust, Respect, Integrity, Diversity, and Entrepreneurship (STRIDE), we create an environment where collaboration thrives, ideas flourish, and transformative changes happen. STRIDE represents more than just letters; it embodies our shared identity and drives our mission. We are dedicated to developing breakthrough therapies that transform patients’ lives, advancing medicine, and supporting one another in these pursuits.

Immunocore is proud to be an equal opportunity employer. As such, we are committed to fostering an inclusive workplace where everyone feels valued, respected, and empowered. We encourage applications from individuals of all backgrounds, regardless of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, or any other characteristic protected by law.