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# Staff Platform Engineer - AI

- **Company:** Datavant
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $220,000.0 - $270,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Engineering, Cursor (Graphical User Interface Elements), Software Design Documents, Key Management, OAuth, Product Software Implementation Methods, Large Language Models, AI Platforms, Kubernetes
- **Published:** June 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0f093956c8f3d6d6

## About the Role

Do you have experience in Software implementation?, * Ten or more years as a software engineer building production platforms, with at least three at Staff IC level or equivalent technical-lead seniority.

 * Deep experience designing and operating cloud-native, Kubernetes-based platforms in production. AWS experience is a plus.
 * Hands-on fluency with at least one mainstream LLM application stack (LangGraph, Bedrock AgentCore, or equivalent), or strong adjacent platform experience plus willingness to learn quickly.
 * Depth in workload identity and access management: service identity, short-lived credentials and token exchange, and key management (SPIFFE/SPIRE, OAuth token exchange, KMS-backed signing, or equivalent).
 * Strong written communication. Architecture decision records and design documents are reviewed before implementation begins on this team.
 * You operate as a peer to senior engineers and leaders outside your team, not as a customer.
 * Personal experience using AI tools in your own engineering work (Claude Code, Cursor, custom MCP servers, agentic side projects, or similar) is valued. We want teammates who use the tools they build platforms for.
 * Healthcare data experience (PHI, HIPAA, BAA workflows) or other regulated-platform background (FedRAMP, HITRUST / HITRUST AI, NIST AI RMF, SOC 2 Type 2) is a strong plus.

## Description

* Help shape the AI Platform's core architecture alongside the VP of AI Platform Engineering and a small group of senior engineers.
 * Establish the platform's technical contracts: how agents register, how they prove identity, how their actions get attributed, audited, and constrained at runtime.
 * Set the technical bar for the team. Mentor two to three engineers, review the work that ships, and author the design documents future hires will read to understand how things are built.
 * Design how the AI Platform interlocks with the rest of engineering: the platform teams whose substrate it builds on, and the product teams whose work it serves.
 * Carry the pager. Operate what you build.


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