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# Staff AI Platform Engineer

- **Company:** Abbott Laboratories
- **Location:** North Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $129,300.0 - $258,700.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Cloud Foundry, Code Review, Continuous Integration, Software Design Documents, Distributed Systems, Python (Programming Language), Network Control, Systems Development Life Cycle, Cloud Services, Azure Machine Learning, Software Engineering, TypeScript, AI Infrastructure, Retrieval-Augmented Generation, Prompt Engineering, Agentic-AI, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Artificial Intelligence Governance, Api Design, Dynatrace, GXP
- **Published:** October 18, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3456065366&tx=IT878TYI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 8-10 years of software engineering, platform engineering, distributed systems, or infrastructure experience, with a track record of owning significant technical scope.
 * Hands-on experience designing and operating enterprise AI/GenAI platforms or comparable developer, data, or ML platforms in production at scale.
 * Strong software engineering ability in Python and at least one of TypeScript, Go, or Java, including distributed systems, API design, testing, and secure SDLC.
 * Deep technical understanding of at least two of: model gateways, GenAI runtimes, RAG, agent/model registries, evaluation, observability/tracing, guardrails, or platform governance.
 * Experience with containers and orchestration (e.g., Kubernetes), infrastructure as code, CI/CD, cloud services, and production SLO/on-call practices, including leading incident response.
 * Bachelor's degree in a related field or equivalent professional experience.
 * Demonstrated ability to drive technical decisions with significant autonomy, influence engineers outside a direct reporting line, and communicate clearly with technical leadership.

Preferred Qualifications

 * Experience building enterprise GenAI or agent platforms using capabilities such as multi-model routing, agent registries, prompt management, evaluation harnesses, and GenAI tracing.
 * Experience in a highly regulated environment such as health tech, med-tech, or life sciences, with GxP, HIPAA, validation, and change-control constraints.
 * Experience implementing security, responsible-AI, privacy, policy, or cost/FinOps controls for shared AI infrastructure.
 * Experience with open standards and tooling such as MCP, OpenTelemetry, Kubernetes, and cloud-native platform engineering practices; prior informal technical leadership or mentoring track record.

## Description

A senior individual-contributor engineering role that drives architecture and delivery for significant portions of Abbott's enterprise AI Platform . This role sets technical direction for one or more platform capability areas, partners closely with the Tech Lead/Architect on reference architecture decisions, and is a primary technical escalation point for consuming teams. Expected to operate with substantial autonomy and to raise the technical bar for the team.

What You'll Do

 * Lead the design of major platform capabilities (e.g., multi-provider model gateway, GenAI runtime, agent/model registries, evaluation and tracing pipelines) with minimal oversight, in partnership with the Tech Lead/Architect.
 * Make and document architecture decisions and tradeoffs for the platform's control plane, paved-road SDKs, and developer experience, weighing scalability, security, cost, and operability.
 * Drive platform observability and evaluation strategy, including distributed tracing, quality/drift/latency/cost signals, and standards other engineers build against.
 * Lead implementation of security, guardrails, and responsible-AI controls (PII/PHI handling, prompt-injection defenses, identity-on-behalf-of, policy enforcement) across platform services.
 * Own platform reliability engineering: define SLOs, lead incident response for high-severity issues, drive root-cause analysis, and improve resilience.
 * Set engineering standards through architecture reviews, design docs, and code reviews; identify and resolve systemic technical risk before it blocks delivery.
 * Make build-versus-buy and vendor recommendations with cost/tradeoff analysis, in partnership with the Tech Lead/Architect and Product Manager.
 * Mentor and technically develop mid-level and junior engineers; act as a technical lead on cross-team initiatives without formal people-management responsibility.
 * Partner with the Product Manager, AI Platform to sequence roadmap, and directly engage senior stakeholders across AI/Agentic Engineering, Applied Data Science, and security on feasibility and design.