Senior AI Architect (US)

Role overview Set the technical direction for a shared AI platform that enables engineering teams to build and operate agents and generative AI solutions. The architect will shape the platform’s runtime, model access, integration, evaluation, and monitoring foundations, along with the standards that help teams use them safely and consistently. The role is listed as remote; periodic travel to offices for team events and onboarding may be required.

Responsibilities - Design and evolve platform architecture for agent execution, MCP integrations, model access, evaluation, and observability as adoption grows. - Lead architecture decisions, design reviews, and hands-on technical mentorship for the AI engineering team. - Translate product roadmaps into architectural needs and document key designs and trade-offs. - Provide reference architectures, reusable patterns, templates, APIs, and guidance to teams building on the platform. - Establish and review standards for security, responsible AI, evaluation, and operational readiness.

Requirements - 12+ years of software engineering and platform architecture experience, including deep cloud expertise; Azure is preferred. - At least 5 years focused on AI/ML infrastructure and generative AI solutions at scale. - Hands-on knowledge of agent systems, orchestration, MCP, tool use, retrieval-augmented generation, vector databases, and production LLM operations. - Experience designing internal platforms with strong developer experience, APIs or SDKs, and self-service capabilities. - Broad understanding of cloud-native and distributed systems, data platforms, and security architecture. - Ability to produce clear architecture documents and explain trade-offs to technical and product audiences.

Nice to have Experience with Azure OpenAI, AKS, API Management, and Databricks; healthcare platforms or clinical workflows; leading a platform engineering team; advanced agent orchestration, MCP server design, agent evaluation, or model fine-tuning; and AI governance or model risk management in regulated settings.

Benefits and work setup Benefits listed include retirement plan matching, flexible paid time off, wellness resources, caregiver and parental leave, fertility and adoption support, development assistance, and employee support programs. Remote roles may require travel to offices for onboarding and team meetings.