Base: $134,866.40 to $202,299.60 annually; bonus/e...
Hybrid
2+ years deploying generative ai agents in production
Expertise in aws, docker, and kubernetes
Proficiency with langchain, langgraph, and rag pipelines
This role involves leading the development of AI operations systems for clinical trial design and operational optimization within a newly formed ML/AI Ops platform team
Job Summary
This role involves leading the development of AI operations systems for clinical trial design and operational optimization within a newly formed ML/AI Ops platform team.
The position requires deep expertise in cloud-native agentic Generative AI deployment methodologies, including managing LLM proxies, RAG pipelines, and token usage monitoring.
AstraZeneca offers a comprehensive relocation package and a competitive annual base pay ranging from $134,866.40 to $202,299.60 for qualified candidates.
Matching Summary
This role involves leading the development of AI operations systems for clinical trial design and operational optimization within a newly formed ML/AI Ops platform team.
Salary
Base: $134,866.40 to $202,299.60 annually; Bonus/Equity: Short-term incentive bonus and equity-based long-term incentive program eligibility; Benefits: 401(k), paid vacation, health/dental/vision coverage
Skills & Requirements
Must-have
2+ years deploying Generative AI agents in production
Expertise in AWS, Docker, and Kubernetes
Proficiency with LangChain, LangGraph, and RAG pipelines
Strong Python and TypeScript software engineering skills
Experience with LLM evaluation tools like Arize Phoenix
Nice-to-have
Knowledge of Good Machine Learning Practice (GMLP)
Familiarity with Vertex AI and Azure Foundry
Understanding of clinical trial design and planning
Ability to work collaboratively in a hybrid team culture
Experience with infrastructure-as-code and CI/CD pipelines
Key Requirements
Minimum 2 years of GenAI agent deployment experience
Deep understanding of Data Science Lifecycle (DSLC)
Expert knowledge of CDK for Python or TypeScript
Proven track record of deploying ML models to production