Principal AI/Agentic Engineer

Abbott

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Abbott Park, IL
Salary
$149,300–$298,700 / yr
Employment
Full-time
Posted
14 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $217k
This role $224k
$125k $317k
below market most similar roles pay here above market

This role pays more than 65% of similar roles. Most pay $180,000–$254,487 — the blue band above. At the midpoint, this role pays about $224k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Abbott

Abbott Laboratories is a global healthcare company that manufactures and markets a broad and diversified line of health care products including diagnostics, medical devices, nutritionals, and branded generic pharmaceuticals. Industry: Healthcare & Medical Devices

Abbott currently has 195 open roles on FindRole.

Listed pay typically runs $99,300–$198,700 across 124 roles with salary data.

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View all roles at Abbott

At a glance

TL;DR · Principal AI/Agentic Engineer

The Principal AI/Agentic Engineer joins the BTS Business Technology Services team to build production-grade agentic systems on the enterprise AI Platform. This player-coach role involves leading a team of engineers to transform business requirements into reliable single- and multi-agent solutions. Key responsibilities include designing durable workflows with persistent state, engineering tool integrations with enterprise systems, and developing context-engineering strategies for retrieval and indexing. You will build evaluation systems using LLM-as-judge metrics and instrument applications for observability. The role requires proficiency in Python and at least one of TypeScript, Go, or Java to develop production code. You will solve complex problems regarding agent architecture, multi-agent coordination, and production reliability within a highly regulated health tech environment, ensuring safety, latency optimization, and secure software engineering practices.

What you'll do

  • Design and operate production agentic systems including supervisor, planner, and multi-agent patterns with human oversight.
  • Build durable, resumable workflows with persistent state, checkpoints, and human-in-the-loop controls.
  • Engineer tool and function integrations with enterprise systems using schemas, authorization, and failure containment.
  • Develop context-engineering strategies for retrieval, chunking, indexing, memory hierarchies, and structured outputs.
  • Create evaluation systems using curated datasets, safety metrics, and LLM-as-judge programmatic evaluators.
  • Instrument agent applications through registries and tracing services to monitor prompts, costs, and latency.
  • Engineer for production reliability including streaming, concurrency, rate limits, and incident response.
  • Hire, coach, and develop a team of agentic engineers while writing and reviewing production code in Python.

What we're looking for

  • 10–15+ years of software engineering experience in 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.
  • Strong understanding of agent architecture, tool calling, durable state, multi-agent coordination, context engineering, retrieval, evaluation, observability, and safety controls.
  • Proficiency in Python and at least one of TypeScript, Go, or Java, including APIs, distributed systems, CI/CD, and secure SDLC.
  • Experience defining and using measurable quality, safety, reliability, latency, and cost indicators to improve systems through iterative releases.
  • Bachelor's degree in a related field or equivalent professional experience.
  • Demonstrated ability to lead engineers, make technical decisions under uncertainty, and communicate with technical and non-technical stakeholders.
  • Experience with agent frameworks, durable workflow systems, or highly regulated environments like health tech (preferred).

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