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Salary
$65k – $156k per year (Estimated)
Location
In office (Osaka, Tokyo)
Seniority
Staff · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
AstraZeneca is a British-Swedish pharmaceutical company formed in 1999 by the merger of Astra of Sweden and Zeneca of the United Kingdom, and now one of the largest drug makers in the world by revenue. Its portfolio is concentrated in oncology with Tagrisso, Imfinzi and Enhertu, alongside cardiovascular, renal and metabolic products including Farxiga, respiratory and immunology medicines, and a rare disease business built on the acquisition of Alexion. Headquartered in Cambridge in England and listed in London, Stockholm and New York, it reports in United States dollars.

Job Description

The Agentic AI Lead is the senior hands-on engineer in the Enterprise AI Technology Delivery team. The role designs, builds, evaluates and operates GenAI and agentic AI systems that AstraZeneca Japan's commercial, medical and field organizations rely on in production, and raises the engineering practice of the team that builds them. This is a building role: the majority of the Lead's time is spent in code, traces and evaluation data, not in coordination.

The Lead takes ownership of the team's existing AI platform assets and key systems for business users. The Lead is also accountable for their reliability, cost and security. The Lead works autonomously with limited supervision, provides technical direction and coaching to the team's AI engineers, and partners with business owners to make sure what gets built solves a validated business problem.

Experience

Mandatory

1. 5+ years building and running software in production (Python; AWS or equivalent cloud).

2. 2+ years hands-on shipping LLM-based or agentic applications to real users, not only proofs of concept.

3. Evaluation-driven practice: can show an evaluation set, error analysis and the iteration it drove on a real project.

4. Daily use of agentic coding tools (Claude Code, Codex or equivalent) as a core part of engineering work, including reviewing and testing their output.

5. Experience leading a technical workstream or mentoring engineers (formal team-lead experience not required; this is a hands-on role, ~80% coding / 20% coordination, suited to a strong developer ready to grow into a lead).

Nice to have

Trained, evaluated or maintained supervised or deep-learning models in production.

Experience in pharma or another regulated industry .

Experience co-developing with external delivery partners or vendors.

Front-end development (React/Next.js) for agent user interfaces.

License

Mandatory

None. Bachelor's degree in Computer Science or a related quantitative discipline, or equivalent experience.

Nice to have

AWS certification (Solutions Architect Associate or Developer Associate, or higher).

Master's or PhD in Computer Science or a related quantitative discipline.

DeepLearning.AI or equivalent LLM/agentic AI coursework.

Skill-set

Mandatory

Agent architecture: workflow vs. agent harness, tool calling, MCP, memory and context management, guardrails against prompt injection and data exfiltration.

At least one agent framework ( Bedrock AgentCore, LangGraph, OpenAI Agents SDK, or equivalent).

Grounding: RAG with vector stores and retrieval over structured data via SQL.

LLM foundations: model selection, tokenisation and cost, context window and caching, when to fine-tune or self-host.

Production operations for AI systems: observability and tracing, cost/latency optimisation, statistical regression testing in CI/CD, prompt/model versioning, infrastructure-as-code.

Software engineering fundamentals: full-stack application design, data modelling, testing strategy, secure-by-design practice (dependency scanning, secrets hygiene).

AWS in production: Lambda, ECS/Fargate, API Gateway, Bedrock, IAM.

Clear written and verbal explanation of technical trade-offs and uncertainty to non-specialists.

Nice to have

Knowledge graphs or semantic layers over structured data (e.g. Snowflake).

Document-processing pipelines for Japanese-language material.

Customising agent environments: skills, MCP servers, hooks, shared context files (CLAUDE.md/AGENTS.md).

Eval/tracing tooling such as Langfuse, Braintrust or LangSmith.

Azure OpenAI and multi-provider gateway experience.

Languages

Mandatory

Japanese:Business level. For non-native speakers: JLPT N2 or higher (N1 preferred).

Native-level Japanese for business stakeholdesr

English:Business level (technical documentation, working with global AZ teams).

Date Posted

17-9月-2026

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.

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