Principal AI/Agentic Engineer

Abbott; Illinois; On-site; USD 149,000 - 299,000; Full time

Job summary

Abbott is seeking a hands‑on software engineering leader to build production‑grade agentic systems on the Abbott enterprise AI Platform. The role is director‑mapped, starting as a player‑coach, delivering and setting technical standards while growing a team of agentic engineers.

You will design, implement, and operate agentic workflows, ensure durability, safety, and observability, and mentor a team of 3–8 engineers across collaborating groups including AI Product Management and security.

Qualifications

• 10–15+ years of software engineering experience with distributed, API‑driven, or workflow‑intensive systems.
• Hands‑on experience building agentic or LLM‑based applications in production and remaining an active contributor.
• Strong understanding of agent architecture, context engineering, observability, safety controls, and multi‑agent coordination.
• Proficiency in Python and at least one of TypeScript, Go, or Java, including CI/CD and secure SDLC.
• Experience defining measurable quality, latency, cost indicators and improving systems iteratively.
• Bachelor's degree or equivalent professional experience and proven leadership of engineers.

Responsibilities

• Lead the delivery of agentic systems and establish technical standards.
• Build and manage a team of approximately 3–8 engineers; hire and coach.
• Design, implement, and operate production agentic workflows with durable state.
• Collaborate with AI Product Management, Platform Engineering, and Security.
• Communicate feasibility, risks, and delivery commitments to stakeholders.

Skills

Leadership

Distributed systems

Python

TypeScript

Go

Java

CI/CD

Observability

Safety controls

API design

Education

Bachelor's degree in a related field

Tools

Python

TypeScript

Go

Java

Job description

About Abbott

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.

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, and safety controls.
• Strong software engineering ability in Python and at least one of TypeScript, Go, or Java, including APIs, distributed systems, CI/CD, testing, code review, and secure SDLC.
• Experience defining measurable quality, safety, reliability, latency, and cost indicators and using evaluation results to improve systems through iterative releases.
• Bachelor's degree in a related field or equivalent professional experience.
• Demonstrated ability to lead engineers, make sound technical decisions under uncertainty, and communicate effectively with technical and non‑technical stakeholders.

Preferred Qualifications

• Experience with agent frameworks or durable workflow systems (e.g., LangGraph, Temporal, or comparable technologies) and model‑provider APIs.
• Experience in a highly regulated environment such as health tech, med‑tech, or life sciences, including GxP, HIPAA, validation, auditability, and change‑control constraints.
• Experience building secure tool‑use systems, prompt‑injection defenses, human‑approval workflows, responsible‑AI controls, and privacy‑preserving agent experiences.
• Experience shipping reusable agent patterns, evaluation tooling, SDKs, or paved‑road capabilities for multiple product or engineering teams.

The base pay for this position is $149,300.00 – $298,700.00. In specific locations, the pay range may vary from the range posted.