Solution Architect, AI & Cloud

This is an individual-contributor role with a clear path to broader player-coach leadership. You will keep writing production code while you set direction, improve engineering practices, and coach the engineers you work with.

In the first six months you take hands-on ownership of our newest AI platform: a Python and FastAPI service on Amazon Bedrock, with a React and TypeScript front end and AWS serverless infrastructure. It turns claim referrals, including PDFs, scanned images, and email, into structured cases and recommended investigative services.

As you establish context, your scope expands to architectural ownership and technical leadership across the other two production systems. Case management is .NET 8 and ASP.NET Core, SQL Server, and Vue 3, covering investigators, scheduling, documents, billing, and client communication. Video is a .NET API, an Angular front end, and a Python GPU service, on AWS media services, for upload, processing, playback, archive, and AI-assisted search.

You work with our development partners and report to the CTO. The work is remote. Candidates in North Carolina, or able to be in Charlotte occasionally, are preferred., * Own the API, infrastructure, and user interface across development, QA, and production.

• Build and operate Python and FastAPI services that use Amazon Bedrock, including multimodal models, for document extraction and service recommendations.
• Maintain the AWS infrastructure, built with SAM and CloudFormation: API Gateway, Lambda, Aurora PostgreSQL Serverless, S3, SQS, DynamoDB, and ECS.
• Guide the React and TypeScript front end, including single sign-on with the case-management platform.
• Make early AI behavior reliable, measurable, and cost-aware. A person reviews every AI output before it is used.

Architecture across case management and video

• Architect the .NET 8 case-management back end and Vue 3 front end, including SQL Server, authentication, and Bedrock-enabled features.
• Modernize a large, business-critical platform in increments, without disrupting daily operations.
• Guide the video API, Angular front end, and Python GPU search service.
• Shape media workflows on S3, DynamoDB, CloudFront, MediaConvert, Step Functions, Lambda, and WebSockets, including storage lifecycle and cost.

Engineering direction

• Set reference patterns, coding standards, security baselines, observability, and CI/CD practice across Azure DevOps and GitHub.
• Lead architecture reviews and write the design notes and decision records the work needs.
• Own cross-platform integration: shared single sign-on, case and video linkage, and the data flows between the systems.
• Coach engineers, support hiring and onboarding, and raise delivery judgment on the team.
• Partner with operations and leadership on priorities, estimates, risks, and tradeoffs., * First 90 days: own the AI platform, ship features and fixes independently, make deployments predictable and documented, and address open security-review items.
• First 6 months: that platform is stable in production, engineering standards are in writing, and you are in regular architecture reviews on the case-management and video systems.
• First 12 months: you are the technical lead across all three, with a cross-platform roadmap and measurable gains in reliability and delivery.

• 12 or more years of professional software engineering, including technical ownership of production systems, not design-only work.
• A player-coach record: substantial production delivery, plus technical leadership and mentoring.
• Strong production experience with C# / .NET and ASP.NET Core, and with Python and FastAPI or a comparable framework.
• Strong TypeScript experience and at least one of React, Vue, or Angular, with the ability to review work in the others.
• Deep AWS experience, including ECS, Lambda, API Gateway, S3, DynamoDB, RDS or Aurora, CloudFront, SQS, Step Functions, IAM, and VPC networking.
• Infrastructure as code, containerized deployment, and performance tuning in SQL Server and PostgreSQL.
• OIDC and OAuth2, JWT, cross-application single sign-on, least-privilege IAM, and secure file handling.
• Proven modernization of a legacy system without stopping the business.
• Clear writing and speech, including explaining a tradeoff to a non-engineer., * Production generative AI, ideally Amazon Bedrock: multimodal prompting, evaluation, document extraction, and cost control.
• Video or media pipelines, HLS, MediaConvert, CloudFront signed access, and S3 lifecycle or archival strategies.
• Computer vision or GPU workloads, such as InsightFace, ONNX Runtime, CUDA, or GPU containers on ECS.
• Azure DevOps, GitHub workflows, NetSuite, Twilio, or Microsoft Graph.
• Insurance, claims, investigations, or another regulated domain with sensitive personal data and evidence.
• Using AI-assisted development tools to raise your own output and the team’s.