Remote Position
[Remote] Senior AI Engineer
🌍 Remote · United States
💼 Full-time
Note: The job is a remote job and is open to candidates in USA. Sedgwick Claims Management Services Inc. is hiring a Senior AI Engineer to build, deploy, and operate production generative AI applications and supporting full-stack services. The role partners with business users and vendor teams, integrates AI with enterprise systems, and ensures production solutions meet security, auditability, and reliability requirements.
Responsibilities
- Owns a build stream end to end within a pod: problem shaping with the Principal, implementation, production operation, and instrumentation of the outcome the business said it would measure
- Designs, builds, and operates production Generative AI agents, workflows, and applications — including request orchestration, tool execution, state management, and interaction with enterprise systems
- Develops full-stack software in Python and React, shipping both the service and the interface a business user touches
- Owns deployment and operation on AWS, with infrastructure as code in Terraform and CI/CD in GitHub Actions, including environments, secrets, and repeatable promotion to production
- Implements evaluation, observability, and human-in-the-loop controls for AI systems: provenance on material outputs, confirmation on consequential claims actions, and evidence that a workflow is ready to move up the autonomy ladder
- Implements authentication, authorization, logging, monitoring, and error handling to meet enterprise security, auditability, PHI, and reliability requirements
- Integrates AI services with enterprise and legacy systems — including APIs, data platforms, and event streams — using approved, non-invasive patterns and versioned contracts
- Stewards a shared capability as assigned (context, documents, agents, or assurance), with authority to block a duplicate build in another pod
- Embeds with vendor delivery teams for co-development when the stream requires it: shared repositories in Sedgwick accounts, shared definition of done, not acceptance testing after a demo
- Sits with examiners, nurse reviewers, or operations staff; watches the work; and turns that into scoped services, workflows, and UI changes
- Provides technical guidance and mentoring to Junior AI Engineers, promoting engineering standards, code quality, and operational excellence
- Troubleshoots and leads root cause analysis and performance optimization for latency, throughput, cost, correctness, and reliability of production AI services
- Evaluates and recommends improvements to architecture, platform capabilities, and engineering process for the stream and the shared substrate
- Performs other duties as assigned
- Travel as required, including on-site work with claims or Managed Care operations and with vendor delivery teams
Skills
- Bachelor's degree in Computer Science, Engineering, or a related quantitative discipline from an accredited college or university required
- Six (6) + years of software engineering experience, with at least three (3) years shipping production Generative AI agents, workflows, or applications — including evaluation, failure handling, and a human review loop — or an equivalent combination of education and experience
- Hands-on experience building and operating production workloads on AWS required. Cloud certification without production ownership is not sufficient
- Hands-on experience with Python, React, GitHub Actions, and Terraform required, including ownership of CI/CD and infrastructure rather than editing templates
- Strong full-stack engineering skills in Python and React, with solid working knowledge of SQL, REST APIs, and service design
- Hands-on AWS: has built, deployed, and operated production services, including networking, identity, and operational concerns sufficient for a regulated environment
- Hands-on GitHub Actions and Terraform: owns pipelines and infrastructure as code, including review, drift, and recovery
- Production command of Generative AI agents, workflows, and applications — tool use, orchestration, evaluation, and human-in-the-loop patterns — sufficient to ship and run, not only prototype
- Ability to implement services in alignment with enterprise architecture, governance, PHI handling, and compliance requirements
- Ability to sit with examiners or operations staff and leave with scoped work; comfortable as the only engineer in that room
- Ability to work collaboratively in a fast-paced Transformation Office, including pairing with vendor engineers when required
- Strong mentoring, collaboration, and technical communication skills
- Ability to meet or exceed Performance Competencies
- Master's degree preferred
- Experience embedding with business users or a vendor delivery team to co-develop, rather than receiving a completed specification, preferred
- Experience in insurance, claims, healthcare, or another heavily regulated operational domain preferred
- Experience with machine learning, model fine-tuning, and/or graph databases (e.g. Neo4j) preferred
- Experience with PydanticAI (or equivalent agent framework), agent observability, and AI Ops / LLMOps a plus
Benefits
- Remote role open to all U.S. states.
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