Staff AI/Agentic Engineer

Abbott • Chicago, IL

16h • Onsite

About The Position

Abbott is hiring a senior individual-contributor engineer to set technical direction for production agentic systems. The role leads the design of complex multi-agent solutions and reusable engineering patterns, partners with the Tech Lead/Architect on architecture decisions, and serves as a primary technical escalation point across the AI/Agentic Engineering team. It operates with substantial autonomy and is expected to raise the team’s technical bar.

The engineer leads development of multi-agent systems, durable workflows, context and retrieval strategies, evaluation approaches, and production reliability practices. They establish engineering standards and create reusable agent patterns, SDKs, and evaluation tools in partnership with AI Platform Engineering. The role also leads technical discovery with product, platform, data science, and business stakeholders, communicates directly with senior stakeholders, and mentors engineers without formal people-management responsibility.

This is an onsite role at an Abbott location in Illinois and is not remote. Travel is 10% of the time. The posted base pay range is $113,300–$226,700, with possible variation in specific locations.

Requirements

• 7–10 years of software engineering experience, including substantial delivery of distributed, API-driven, or workflow-intensive production systems.
• Hands-on experience designing, coding, testing, deploying, and operating agentic or LLM-based applications in production at scale, while remaining an active technical contributor.
• Deep 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 distributed systems, API design, testing, and secure SDLC.
• Experience defining measurable quality, safety, reliability, latency, and cost indicators and using evaluation results to drive systemic improvement across multiple workflows.
• Bachelor’s degree in a related field or equivalent professional experience.
• Ability to drive technical decisions with significant autonomy, influence engineers outside a direct reporting line, and communicate effectively with technical leadership.

Nice To Haves

• Experience with agent frameworks or durable workflow systems such as LangGraph, Temporal, or comparable technologies, and model-provider APIs at scale.
• Experience in a highly regulated environment such as health tech, med-tech, or life sciences, including GxP, HIPAA, validation, and change-control constraints.
• Experience building secure tool-use systems, prompt-injection defenses, human-approval workflows, and responsible-AI controls for production agentic systems.
• Track record of shipping reusable agent patterns, evaluation tooling, or paved-road capabilities adopted by multiple teams.
• Prior informal technical leadership or mentoring experience.

Responsibilities

• Lead the design and implementation of complex multi-agent systems, including supervisor, planner/executor, and coordination patterns with clear boundaries and failure handling.
• Set standards for durable workflow design, including state, checkpoints, replay, idempotency, compensation, and human-in-the-loop processes.
• Drive context-engineering and retrieval strategies across workflows, including chunking, indexing, memory hierarchies, grounding, and context-window budgeting.
• Lead evaluation strategy by designing evaluation systems, curating datasets, defining task-success and safety metrics, and establishing regression gates in CI and online or shadow evaluation.
• Own production reliability for high-complexity or high-risk agentic systems, including latency and cost optimization, rate-limit strategy, graceful degradation, and incident response leadership.
• Set engineering standards through architecture reviews, design documents, and code reviews; identify and resolve systemic technical risks in agent delivery.
• Create reusable agent patterns, SDKs, and evaluation tooling for the platform paved road in partnership with AI Platform Engineering.
• Lead technical discovery with AI Product Managers, Platform Engineering, Applied Data Science, and business stakeholders; communicate feasibility, risk, and delivery commitments to senior stakeholders.
• Mentor and technically develop mid-level and junior engineers, and act as technical lead on cross-team initiatives without formal people-management responsibility.

Benefits

• Career development with an international company.
• Employees can qualify for free medical coverage in the Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• Retirement savings plan with a high employer contribution.
• Tuition reimbursement.
• Freedom 2 Save student debt program.
• FreeU education benefit, an affordable and convenient path to earning a bachelor’s degree.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior