Staff AI Platform Engineer

Abbott (abbottcareers2 board); Illinois; On-site; USD 190,000 - 260,000; Full time

Benefits offered by this job

HIP PPO medical plan

Excellent retirement plan

Tuition reimbursement

FreeU education benefit

Great place to work

Job summary

Abbott is seeking a senior platform engineer to drive architecture and delivery for significant portions of our enterprise AI Platform. You will set technical direction, partner with Tech Lead/Architect, and be a primary escalation point for consuming teams.

You will lead design efforts for major platform capabilities, document tradeoffs, and ensure scalability, security, and cost efficiency while mentoring mid-level and junior engineers across cross-team initiatives.

Qualifications

• 8–10 years in software/platform engineering.
• Experience with GenAI platforms in production.
• Proficiency in Python and at least one of TypeScript/Go/Java.
• Experience with containers, Kubernetes, IaC, CI/CD, and cloud services.
• Bachelor's degree or equivalent.
• Ability to drive technical decisions with autonomy and influence across teams.

Responsibilities

• Lead design of major platform capabilities (multi-provider model gateway, GenAI runtime, registries) with minimal oversight.
• Document architecture decisions balancing scalability, security, cost, and operability.
• Define observability and evaluation strategy with tracing, latency, and cost signals.
• Implement security, guardrails, and responsible-AI controls across services.
• Own platform reliability: set SLOs, lead incident response, drive postmortems.
• Set engineering standards via reviews and architecture decisions.

Skills

Software engineering

Platform engineering

Distributed systems

Python

TypeScript/Go/Java

Kubernetes

Education

Bachelor's degree

Tools

Kubernetes

Terraform

Docker

Job description

JOB DESCRIPTION:

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.

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You'll also have access to:

• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution
• Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor's degree.
• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
• A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

The Opportunity

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.

Education and Experience You'll Bring

Required Qualifications

• 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/