Principal AI Engineer

Sedgwick•Telecommuter FL, FL

4d•Remote

About The Position

The Principal AI Engineer owns the technical outcome of a value-stream pod from problem shaping through production operation. The role partners directly with business transformation leadership and claims and Managed Care operations, works with users to shape ambiguous problems, and ensures work contributes to shared capabilities rather than duplicating or extending broken processes. The engineer architects and personally builds production generative AI agents, workflows, and applications, writing Python and React code. This role sets engineering standards for the pod, including API-first and contract-first delivery, AWS and Terraform for production, GitHub Actions for CI/CD, evaluation and observability as release gates, and human confirmation for consequential claims actions. It stewards shared AI platform capabilities, may block duplicate builds, and establishes vendor delivery terms when work is co-developed. The engineer defines evaluation, provenance, and autonomy-ladder evidence for AI workflows, with business stakeholders owning thresholds, and escalates conflicts with enterprise standards such as identity, model egress, PHI, and portability. The Principal AI Engineer represents the pod on the AI Engineering design council, works independently with peer Principals, mentors Senior and Junior AI Engineers, and leads complex troubleshooting, root cause analysis, and performance optimization. The role evaluates whether capabilities should be built in-house, co-developed with a vendor, or not built, and ensures accepted compromises have a named owner and removal path. Travel is required as needed, including regular onsite work with claims or Managed Care operations and vendor delivery teams.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related quantitative discipline from an accredited college or university.
At least 10 years of software engineering experience, including at least four years owning production generative AI or applied-AI systems in the field, or an equivalent combination of education and experience.
Hands-on production experience on AWS and hands-on skills in Python, React, GitHub Actions, and Terraform sufficient to set standards for a pod.
Experience leading technical delivery for a value stream or equivalent without people-management authority.
Expert full-stack engineering skills in Python and React, with strong SQL, API, and service-design skills; must still write production code.
Deep hands-on AWS, Terraform, and GitHub Actions experience, including identity, networking, environments, and operational recovery.
Production command of generative AI agents, workflows, and applications, including tool use, orchestration, evaluation, provenance, and human-in-the-loop patterns.
Ability to shape problems, scope builds, and define explicit non-goals with examiners or operations leaders.
Ability to keep a pod on shared substrate and stop duplicate builds without escalating every conflict.
Ability to set interface terms with vendors and internal platform teams while remaining an individual contributor rather than their manager.
Strong mentoring, collaboration, and technical communication skills, with ability to influence transformation leadership, architecture, security, and engineering peers.
Ability to meet or exceed Performance Competencies.

Nice To Haves

Master’s degree.
Experience in insurance, claims, healthcare, or another heavily regulated operational domain.
Experience with machine learning, model fine-tuning, and/or graph databases such as Neo4j.
Experience with PydanticAI or an equivalent agent framework, agent observability, and AI Ops / LLMOps.

Responsibilities

Own the technical outcome of a value-stream pod from problem shaping through production operation.
Partner with business transformation leadership, examiners, nurse reviewers, and operations to shape problems and avoid building onto processes known to be broken.
Architect and personally build production generative AI agents, workflows, and applications, contributing Python and React code.
Set and enforce pod engineering standards for API-first and contract-first delivery, AWS, Terraform, GitHub Actions, evaluation, observability, and human confirmation for consequential claims actions.
Ensure the pod uses shared capabilities and block duplicate builds when appropriate.
Define interface terms with vendor delivery teams for co-developed work, including shared repositories, Sedgwick-owned contracts, and a shared definition of done.
Establish evaluation, provenance, and autonomy-ladder evidence for AI workflows, with business stakeholders owning thresholds.
Lead technical solution design and architectural review, and escalate conflicts with enterprise standards.
Represent the pod on the AI Engineering design council and converge with peer Principals on ordinary technical disagreements.
Provide technical guidance and mentoring to Senior and Junior AI Engineers.
Lead complex troubleshooting, root cause analysis, and performance optimization for business-critical AI services and platforms.
Evaluate whether capabilities should be built in-house, co-developed with a vendor, or not built, and define an owner and removal path for accepted compromises.
Perform other duties as assigned.
Travel as required, including regular onsite work with claims or Managed Care operations and vendor delivery teams.