Jobs / United States / Astrazeneca Pharmaceuticals Lp
Associate Director, Clinical AI Translation & Solutions
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 roles4 certified filings for “Associate Director, Precision Medicine” (Medical Scientists, Except Epidemiologists) in MA: $179k–$260k, median $215k. Most were filed at wage level II (75%) — 2 lottery entries, ≈31% 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
Job Title: Director, AI Research Introduction to role: Are you ready to turn complex clinical workflows into safe, measurable AI systems that accelerate trials and meaningfully improve patient outcomes? This role sits at the heart of how we design, conduct, monitor, and analyze clinical studies—translating real-world operations into AI solutions that scale across the enterprise and deliver tangible business value. You will work side-by-side with clinical professionals and engineers to observe how work truly happens, identify where AI can safely help, and translate that understanding into working software. Do you thrive on building hands-on prototypes, making disciplined scope decisions, and staying accountable through evaluation, deployment, adoption, and iteration? Your initial focus will include agentic workflows for clinical operations, with the expectation that reusable patterns will extend across Clinical Development. Accountabilities: • Portfolio Ownership: Own a portfolio of clinical AI workflows from discovery through deployment, adoption, and measurable benefit realization, ensuring early wins become platform capabilities. • Workflow Discovery and Design: Observe CRAs, site-monitoring leaders, clinical operations, and medical stakeholders to convert pain points into product requirements, data contracts, acceptance criteria, and evaluation plans. • Hands-on Prototyping and Delivery: Build and iterate prototypes in Python; contribute production code, review pull requests, inspect logs, reproduce failures, and collaborate with engineers to resolve them. • Agentic Workflow Design: Combine language models, deterministic services, enterprise tools, and human review with clear evidence provenance, uncertainty handling, and fail-safe behavior. • Scope and Release Discipline: Separate demonstrations from production releases and distinguish non-GxP workflows from regulated use, making transparent risk and lifecycle trade-offs. • Outcome Measurement: Define outcome measures spanning technical performance, clinical usefulness, workflow quality, user adoption, cycle time, and operational impact. • Human-in-the-Loop Testing: Lead testing with clinical experts and translate feedback into prioritized, testable product changes that increase trust and adoption. • Data Access and Governance: Partner with data-product owners and platform teams to establish reliable access to clinical systems, documents, and structured data while protecting privacy and integrity. • Compliance by Design: Collaborate with Quality, Regulatory, Privacy, Security, and R&D IT to embed GCP, GxP, validation, auditability, and lifecycle requirements from the outset. • Reuse and Build/Buy Decisions: Promote reuse of enterprise platforms, data products, agent components, and evaluation assets; identify when to build, buy, partner, or adapt. • Communication and Influence: Communicate product decisions, evidence, risks, dependencies, and trade-offs clearly to technical teams, clinical leaders, and executives. • Mentorship and Standards: Mentor scientists and engineers and raise the team’s standard for product thinking, technical execution, and clinical partnership. Essential Skills/Experience: • PhD in Computer Science, Machine Learning, Statistics, Biomedical Informatics, Computational Biology, or a related quantitative discipline; or an MD, master’s degree, or equivalent experience supported by a strong computational track record. • 4 to 7 years of post-PhD (or equivalent) experience delivering applied AI/ML or data products, including experience in healthcare, life sciences, clinical research, or another high-consequence domain. • Current, hands-on coding ability in Python and SQL, with experience using version control, tests, APIs, data pipelines, and