Principal AI Engineer - Remote

Fortune Best Workplaces in Financial Services & Insurance
Principal AI Engineer

Remote role open to all U.Owns the technical outcome of a value-stream pod from problem shaping through production operation, including whether work contributes to shared capability or is incomplete.
Partners directly with business transformation leadership, examiners, nurse reviewers, and operations — sitting with users, shaping ambiguous problems, and refusing work that would wire new capability onto a process known to be broken.
Architects and personally builds production Generative AI agents, workflows, and applications, contributing code in Python and React rather than reviewing from a distance.
Sets and enforces engineering standards for the pod: API-first and contract-first delivery, AWS and Terraform as the path to production, GitHub Actions as the CI/CD bar, evaluation and observability as release gates, and human confirmation on consequential claims actions.
Accountable for whether the pod lands on shared substrate (context, documents, agents, assurance) or forks it; Defines interface terms with vendor delivery teams when the stream is co-developed: shared repositories in Sedgwick accounts, Sedgwick-owned contracts, shared definition of done.
Establishes evaluation, provenance, and autonomy-ladder evidence for AI workflows — what may auto-complete, what must ask then do, and what is not ready — with the business owning thresholds.
Represents the pod on the AI Engineering design council; Provides technical guidance and mentoring to Senior and Junior AI Engineers; raises the pod’s bar on code quality, operational excellence, and forward-deployed practice.
Leads complex troubleshooting, root cause analysis, and performance optimization for business-critical AI services and platforms.
Evaluates and recommends whether a capability should be built in-house, co-developed with a vendor, or not built — with a named owner and a removal path when a compromise is accepted.
Travel as required, including regular on-site work with claims or Managed Care operations and with vendor delivery teams.
Bachelor’s degree in Computer Science, Engineering, or a related quantitative discipline from an accredited college or university required. Ten (10)+ or more years of software engineering experience, including at least four (4) years owning production Generative AI or applied-AI systems in the field — agents, workflows, or applications, including evaluation, failure handling, and a human review loop — or an equivalent combination of education and experience.Hands-on production experience on AWS, and hands-on Python, React, GitHub Actions, and Terraform, at a level sufficient to set the bar for a pod, not only meet it. Cloud certification or architecture-only experience without recent production code is not sufficient.Experience in insurance, claims, healthcare, or another heavily regulated operational domain preferred.
Expert full-stack engineering skills in Python and React, with strong SQL, APIs, and service design; Deep, hands-on AWS, Terraform, and GitHub Actions — including identity, networking, environments, and operational recovery — sufficient to set standards and review others’ work
Production command of Generative AI agents, workflows, and applications, including tool use, orchestration, evaluation, provenance, and human-in-the-loop patterns
Ability to walk into a design session with examiners or operations leaders and leave with a shaped problem, scoped build, and explicit non-goals
Ability to set interface terms with vendors and internal platform teams while remaining a peer IC, not a manager of either
Strong mentoring, collaboration, and technical communication skills with the ability to influence transformation leadership, architecture, security, and engineering peers
Experience with machine learning, model fine-tuning, and/or graph databases (e.g. Experience with PydanticAI (or equivalent agent framework), agent observability, and AI Ops / LLMOps a plus
Ability to meet or exceed Performance Competencies
excellent judgment, troubleshooting, problem solving, analysis, and discretion; Computer keyboarding, travel as required
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