AI Engineer
Design, build, and operationalize agentic AI systems for clinical research, leveraging Python, machine learning, reinforcement learning, and cloud-native tools such as AWS, Docker, and Kubernetes.
We’re on a mission to change the future of clinical research. At Perceptive , we help the
biopharmaceutical industry bring medical
treatments to the market, faster.
Our mission is to change the world
but to do this, we need people like you.
What can we offer you?
Apart from job satisfaction, we can offer you:
YOURSELF • 25 days’ holiday (with the option to buy more)
HEALTH
• Health Cash Plan
• Optional private health, dental insurance, and health screens
• Cycle to work scheme
WEALTH • Generous pension scheme with up to 10% employer contribution • Life assurance
• Season ticket loan
About the role
As Agentic AI Engineer, you will design, build, and operationalize agentic AI capabilities to increase automation, improve data quality, and accelerate decision-making within medical imaging clinical trials. This role focuses on building AI agents that can reliably execute workflows such as intake and validation of imaging data, metadata reconciliation, protocol-driven checks, quality control support, and structured extraction from multi-modal artifacts (DICOM, non‑DICOM, reports, PDFs). In parallel, the role will help transform the company’s Product Development Life Cycle (PDLC) into an AI-driven lifecycle—enabling agentic workflows from Product Discovery (e.g., requirements synthesis, research, backlog shaping) to Delivery and Deployment (e.g., test generation, release readiness, documentation automation) through Production Operations (e.g., incident triage, observability insights, automated runbooks), while ensuring safety, compliance, traceability, and human oversight.
Key Responsibilities
C ross functional collaborations
Partner with Product, Imaging Ops, Data Engineering, QA, Security, and Regulatory/Quality to identify high-value automation opportunities and define agentic AI use cases.
Translate clinical-trial imaging workflows and PDLC processes into agent-ready task models (inputs, outputs, constraints, guardrails, acceptance criteria).
Work with SMEs to define quality rubrics, evaluation datasets, and human review workflows to validate agent outputs.
Support change management: help teams adopt agentic features with clear UX patterns, onboarding, and documentation.
Technical ownership
Promote engineering best practices for agentic systems: reliability, observability, evaluation, reproducibility, and secure-by-design patterns.
Contribute to internal standards for: prompt/version control, agent tools/plugins, retrieval configuration, grounding/citations, and human-in-the-loop review.
Participate in design reviews and provide guidance on selecting frameworks and architectures.
Coach peers
Posted June 27, 2026