Lead Consultant Knowledge graph expert

GCL : E

Introduction to role:

Are you ready to turn knowledge graphs and agentic AI into production products that accelerate how medicines reach patients Do you thrive on moving from idea to working software shipping secure reliable systems that reason plan and act across complex data and tools

In this hands-on role you will lead the design and build of GenAI assistants and agentic solutions that help global supply chain teams plan source and deliver with greater speed and confidence. You will create end-to-end applications that combine RAG and Graph RAG with full-stack engineering and deploy them on AWSbridging pioneering AI with the realities of enterprise operations to deliver measurable impact.

You will join a small multi-functional team where product data science and engineering sit side by side. Here you will turn high-value supply chain problems into scalable AI products moving quickly from PoC to production while building reusable patterns the wider organization can adopt.

• Product Strategy and Alignment: Translate priority supply chain problems into product roadmaps and technical strategies that deliver measurable outcomes (cycle-time reduction service-level improvements transparency for decision-makers).
• Agentic AI Development: Design and implement agents that plans reason and act using tool/function calling and orchestration frameworks (e.g. LangGraph CrewAI AutoGen or Bedrock Agents) including multi-agent workflows where they contribute.
• End-to-End LLM Applications: Build robust RAG and Graph RAG pipelinesembeddings vector search retrieval and re-ranking prompt orchestration and evaluationto ground responses in trustworthy data and supply chain context.
• Knowledge Graph Integration: Model supply chain entities and relationships; integrate graph-based retrieval to power reasoning and traceability across processes and data sources enabling better root-cause analysis and proactive interventions.
• Full-Stack Engineering: Develop back-end services and APIs (Python/Fast-API or ) and front-end applications (React/ TypeScript) that put AI insights and actions in the hands of users.
• Cloud Deployment and Operations: Ship to production on AWS (Bedrock SageMaker Lambda ECS/EKS Open-Search S3) with security observability and cost-awareness built in from day one.
• Move use cases from PoC to services that are resilient and monitored. Define SLIs and SLOs. Implement testing and CI/CD. Use data to guide improvements.
• Reusable Components and Standards: Codify common patterns guardrails and libraries across teams to accelerate delivery and ensure consistent quality.
• Stake-holder Partnership: Work closely with product engineering data science and supply chain leaders to prioritize pilot and scale solutions; communicate trade-offs and guide adoption of AI driven ways of working.

• Strong full-stack software engineering front-end (React / TypeScript) and back-end (Python / FastAPI or ) building and shipping production APIs and apps.
• Hands-on experience building agentic AI solutions LLM agents that use tool calling / function calling planning / reasoning loops and orchestration frameworks (e.g. LangGraph Bedrock Agents); multi-agent design a plus.
• Hands-on GenAI / LLM experience: RAG (embeddings vector databases chunking retrieval re-ranking) and exposure to Graph RAG.
• Solid AWS experience (preferred cloud) e.g. Bedrock SageMaker Lambda containers Open-Search.
• Comfortable across the full SDLC in Agile teams; good communication.
• Product/Project Management experience in Data Analytics & AI solutions
• Bachelors - degree in IT Computer Science Data Analytics or related field.

• Masters - Degree M.B.A or Ph.d in a relevant field
• Knowledge Graph experience with Neo4j or Amazon Neptune (graph modelling Cypher / Gremlin) a strong plus not required; well help you upskill.
• LangChain / Langsmith LLM evaluation and guardrails MLOps / LLMOps and Observability.
• Prompt-engineering fluency and awareness of current GenAI tooling.
• Pharma / regulated-industry or large-enterprise experience.

Join a global community of technologists and data experts working shoulder to shoulder with scientists and supply chain leaders to reshape how medicines are made and delivered. We are investing heavily in modern platforms and AI pairing bold ambition with the support to experiment learn fast and scale what works. Expect unexpected teams in the same room unleashing inventive ideas a thoughtful culture that values kindness alongside drive and clear line of sight from your code to patient outcomes. You will have room to own outcomes tackle complex challenges and grow your craft while helping an entire enterprise become truly data-led.

If you want to build agentic graph-powered AI that ships to production and moves life-changing medicines faster to patients wed love to see how youll lead the way!

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds with as wide a range of perspectives as possible and harnessing industry-leading skills. We believe that the more inclusive we are the better our work will be. We welcome and consider applications to join our team from all qualified candidates regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment) as well as work authorization and employment eligibility verification requirements.