# IT Product Owner, BAIC at AstraZeneca

AstraZeneca is hiring an IT Product Owner, BAIC. Level rates it Works on AI ●●●○; you can [apply on AstraZeneca](https://jobsbylevel.com/go/76a8fed8-5757-4256-a8f2-9eca54c3ddcb?utm_medium=ai-agent).

AI Level 3, AI centrality 75 out of 100. Shanghai Jing'An Office.

## Details

- Company: [AstraZeneca](https://jobsbylevel.com/companies/astrazeneca)
- AI level: AI Level 3 (score 75 out of 100)
- Location: Shanghai Jing'An Office
- Posted: October 29, 2026
- Apply: https://jobsbylevel.com/go/76a8fed8-5757-4256-a8f2-9eca54c3ddcb?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=it-product-owner-baic-at-astrazeneca-3c5bc5

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/it-product-owner-baic-at-astrazeneca-3c5bc5

## Description

DUTIES & RESPONSIBILITES 1. Product Vision, Strategy & Roadmap Define and own the vision, strategy and roadmap for the agent platform, aligned with the BAIC platform strategy and AstraZeneca’s enterprise AI strategy Track the fast-moving agent ecosystem (models, protocols, frameworks, open standards) and decide what to build, buy, adopt or retire; keep the platform modular so components can be swapped as technology changes Translate the needs of agent developers and priority business use cases into an outcome-based roadmap with clear OKRs, release plans and success metrics Communicate the roadmap and trade-offs clearly to BAIC leadership, developer communities and stakeholders 2. Core Agent Capabilities: LLM Gateway, MCP & Memory LLM gateway: own a single, governed entry point to multiple models, with model catalog, routing and fallback, authentication, quotas and rate limits, caching, usage metering and chargeback, logging and content safety controls MCP & tools: own the MCP server registry and gateway, standards for building and certifying MCP servers, and secure identity-aware connectors to AZ systems and data (e.g. R&D data platforms, document and knowledge repositories, business applications) Memory & context: own short- and long-term agent memory, retrieval (RAG) and vector services, and context management, with clear controls for data access, retention and privacy Shape adjacent capabilities as the platform matures: agent runtime and orchestration, agent identity and permissions, agent-to-agent communication, prompt and configuration management 3. Developer Experience & Adoption Treat agent developers as customers: run discovery and feedback loops, and measure developer satisfaction and time-to-first-agent Deliver a strong self-service developer experience : SDKs and APIs, reference architectures, templates, documentation, sandbox environments and simple onboarding Build an internal developer community through demos, office hours, training and champions; drive reuse of shared MCP servers, memory and patterns across teams Track platform adoption (teams, agents in production, API and token usage) and use the data to prioritise the backlog 4. Trust, Security & Governance by Design Embed guardrails in the platform: prompt-injection and data-leakage protection, PII handling, content filtering, tool permission scoping and human-in-the-loop controls Provide observability and evaluation : end-to-end tracing of agent and tool calls, audit trails, quality and safety evaluations, and production monitoring Make Responsible AI and compliance easy to follow: align with AZ AI governance, information security and privacy policies, support CSV/GxP needs for agents used in regulated processes, and meet China requirements on generative AI services, data security and cross-border data transfer Work with security and architecture teams on threat modelling, access reviews and risk acceptance for new capabilities 5. Backlog Ownership & Roadmap Execution Own and prioritise the product backlog ; write epics, user stories and acceptance criteria, including non-functional requirements (latency, availability, scalability, security) Lead Agile delivery with platform engineering squads and vendors/OSPs; make timely scope and release decisions and deliver the roadmap predictably Define and manage platform SLAs/SLOs, versioning and deprecation policies, and backward-compatibility commitments to developers Manage dependencies with cloud, identity, network, data and security teams; manage risks, issues and release readiness 6. Value, Cost & Vendor Management Own the platform budget (annual plan, MTP inputs, forecasting, variance analysis), including model and token spend Apply FinOps for AI : monitor token and compute consumption, optimise model routing and caching, and give consuming teams cost transparency and showback/chargeback Track and report platform value (e.g. development time saved, reuse, cost per agent, reliability) to BAIC leadership

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