Jobs / United States / Astrazeneca Pharmaceuticals Lp
Agentic AI Sr. Engineer
Astrazeneca Pharmaceuticals Lp · 🇺🇸 US - Cambridge Kendall SQ - MA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 99 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Astrazeneca Pharmaceuticals Lp paid sponsored hires in similar roles2 certified filings for “Senior Platform Engineer - CRM Applications” (Information Technology Project Managers) in DE: $149k–$176k, median $163k. Most were filed at wage level III (50%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Astrazeneca Pharmaceuticals Lp
The US Department of Labor certified 99 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Astrazeneca Pharmaceuticals Lp →
About the role
Modality: Hybrid (3 days in office, 2 days remotely) Location: Cambridge, MA or Gaithersburg, MD What You’ll Do • Design, build, and operate the agentic and LLM-powered systems that biologics scientists rely on, owning them from concept through reliable, monitored production use. • Build custom agentic skills and tools that encode our scientists’ expertise, so an agent can do real domain work rather than generic chat. • Connect agents to internal data, models, and services through AZ’s approved integration platforms, in line with AZ data and security standards. • Build and deploy LLM and agentic applications end to end, including the interfaces and the supporting engineering (authentication, logging, evaluation, error handling) that makes a tool dependable. • Build the digital pipelines that move data between our models, our high-throughput and automated lab platforms, and the scientists who use the results. • Partner day to day with protein scientists, computational biologists, and platform engineers, and work in close partnership with BIX, EAI, and R&D IT, reusing shared platforms and data products rather than building in isolation. • Document your work in GitHub and Confluence so others can maintain and extend it, and meet relevant safety, quality, and compliance standards, including FAIR (Findable, Accessible, Interoperable, Reusable) data practices. How You’ll Work You will work in the CLI or the coding environment you prefer, such as VS Code, using code assistants and agents day to day to write and ship code more efficiently. Our stack includes Claude Code, Claude Cowork, GitHub Copilot, M365 Copilot, and HuggingFace, with GitHub and Confluence for code and documentation. You will deploy on AZ infrastructure including scientific computing platforms, AWS, Kubernetes, and Domino, with access to high-end GPU compute (including AZ’s sovereign AI compute platform built on NVIDIA DGX SuperPOD). What You Bring Essential Education & Experience • MS degree in Computer Science, Software Engineering, Computational Biology, Data Science, or a related quantitative field, or equivalent demonstrated ability. • 3–10 years of relevant software engineering experience. • Proven, hands-on experience building agentic AI systems and deploying them to production. We look for something you personally built and shipped that people used, whether at a company, a startup, a lab, or a substantial open-source or personal project. Essential Skills • Solid Python and/or TypeScript programming skills, and hands-on experience in software development best practices: clean code, version control, testing, and the judgment to build something that keeps working after you have moved on. • Practical experience building with LLMs and agent frameworks, including tool and function calling, retrieval, and orchestration of multi-step workflows. • Fluency with modern agentic developer tools such as Claude Code, Copilot, or similar, used daily as part of how you build. • Clear written and verbal communication, with the ability to explain technical choices to scientists who are not engineers. • Working knowledge of Unix, SQL databases, REST APIs, and cloud computing (AWS). Desired Skills • Experience with tool-integration layers that connect agents to enterprise data, models, and services. • Experience with AI frameworks such as Pydantic-AI, LangChain, or similar. • Experience building production retrieval-augmented generation (RAG) pipelines and working with vector databases. • Experience in at least one compiled programming language (e.g., C, Java, Go, or Rust). • Experience with the evaluation and guardrails that make LLM applications trustworthy, and cloud deployment practice: containers, Kube