Principal AI/Agentic Engineer

Thornton Tomasetti; Northern (KY); Hybrid; USD 149,000 - 299,000; Full time

Job summary

Abbott Park, IL seeks a Principal AI/Agentic Engineer to lead production-grade agentic systems on Abbott's enterprise AI Platform. You will translate business needs into reliable single- and multi-agent solutions, starting as a player-coach and guiding a growing team.

You will design and operate agentic workloads, durable workflows, and tool integrations, while ensuring reliability and observability across services.

Qualifications

• 10–15+ years of software engineering with distributed, API-driven production systems.
• Hands-on experience building agentic or LLM-based applications in production.
• Strong understanding of agent architecture, durable state, multi-agent coordination, context engineering, retrieval, observability, and safety controls.
• Bachelor's degree in a related field or equivalent professional experience.

Responsibilities

• Design, implement, and operate production agentic systems with supervision and multi-agent patterns.
• Build durable workflows with persistent state, checkpoints, replay, idempotency, and human-in-the-loop controls.
• Integrate tool calls, contracts, schemas, retries, timeouts, and failure containment with enterprise systems.
• Develop context-engineering strategies covering memory, chunking, budgeting, caching, and grounding.
• Create evaluation systems with curated datasets, automated evaluation, CI gates, and A/B/shadow evaluations.
• Lead a team of 3–8 engineers; set goals, review performance, and share reusable patterns.

Skills

Distributed systems

LLM-based applications

Agent architecture

Python

TypeScript

Go

Java

Education

Bachelor's degree in related field

Tools

Python

TypeScript

Go

Java

Job description

## Principal AI/Agentic EngineerApply: United States - Illinois - Abbott Park: Full time: Posted Today: End Date: October 31, 2026 (18 days left to apply): 31164459Abbott 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, 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