Jobs / United States / Abbott Laboratories
Principal AI/Agentic Engineer
Abbott Laboratories · 🇺🇸 United States - Illinois - Abbott Park
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 73 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 28 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 Abbott Laboratories paid sponsored hires in similar roles1 certified filing for “SENIOR WAN ENGINEER” (Network and Computer Systems Administrators) in IL: $122k–$122k, median $122k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% 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.
Or apply yourself on the official page →
Sponsor Radar — Abbott Laboratories
The US Department of Labor certified 73 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 28 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 Abbott Laboratories →
About the role
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: About Abbott About Abbott (standard corporate boilerplate; pull the current approved version from Talent Acquisition/Brand before external use): Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio spans diagnostics, medical devices, nutritionals, and branded generic medicines, and our colleagues serve people in more than 160 countries. The Opportunity A hands-on software engineering leadership role accountable for building production-grade agentic systems on Abbott's enterprise AI Platform. This role turns business and product requirements into reliable single- and multi-agent solutions, reusable engineering patterns, and measurable outcomes. The role is Director-mapped and begins as a player-coach: it leads delivery and technical standards while building and managing a team of agentic engineers. What You'll Do • Design, implement, and operate production agentic systems, including supervisor, planner/executor, and multi-agent patterns with explicit boundaries, failure handling, and human oversight. • Build durable, resumable workflows with persistent state, checkpoints, replay, idempotency, compensation, and human-in-the-loop controls (e.g., LangGraph- or Temporal-style durable execution). • Engineer tool and function integrations with Abbott enterprise systems, including MCP-style tool contracts, schemas, authorization, retries, timeouts, compensation, and failure containment. • Develop context-engineering strategies covering retrieval, chunking and indexing, memory hierarchies, context-window budgeting, caching, structured outputs, and grounding. • Create evaluation systems with curated datasets, task-success and safety metrics, LLM-as-judge and programmatic evaluators, regression gates in CI, and online, A/B, and shadow evaluation. • Instrument agent applications through the platform's model and agent registries and tracing services so prompts, tool calls, intermediate steps, quality, cost, and latency are observable and auditable. • Engineer for production reliability: streaming, concurrency, latency and token-cost optimization, rate limits, graceful degradation, secure deployment, SLOs, on-call, incident response, and rollback of agent regressions. • Write and review substantial production code in Python and at least one of TypeScript, Go, or Java; establish testing, code review, API design, and secure software engineering practices. • Lead technical discovery and delivery with AI Product Managers, Platform Engineering, Applied Data Science, security, and business stakeholders; communicate feasibility, risks, and delivery commitments. • Hire, coach, and develop a team of approximately 3–8 agentic engineers; set goals, allocate work, review performance, and create reusable patterns that feed back into the platform paved road. Required Qualifications • 10–15+ years of software engineering experience, including substantial delivery of distributed, API-driven, or workflow-intensive production systems and technical leadership. • Hands-on experience designing, coding, testing, deploying, and operating agentic or LLM-based applications in production; this role is expected to remain an active technical contributor. • Strong understanding of agent architecture, tool calling, durable state, multi-agent coordination, context engineering, retrieval, evaluation, observability,