Principal AI Platform Engineer (AI-Native SDLC)

Quick Facts

• Role: Principal AI Platform Engineer (AI-Native SDLC)
• Individual contributor; hands-on technical leader

Description

Lead the technical design of an AI-native software development lifecycle for a developer platform serving thousands of engineers. Define the reference architecture and capability map from requirements through deployment and incident response, including where AI agents operate and where people approve. Build governed SDLC agents and an AI marketplace for discovering and reusing agents, MCP servers, and skills.

Responsibilities

• Define AI-native SDLC reference architecture and capability map across the full lifecycle
• Develop engineering knowledge grounding for AI agents using services, APIs, standards, architecture decisions, and incident history
• Build SDLC agents for PR review, documentation, and rollout risk with evaluation, audit logging, and least-privilege access
• Design an AI marketplace with trust tiers and a path from experimental to supported
• Use Model Context Protocol (MCP) as the standard interface so tools can be replaced without rebuilding the platform
• Partner with security, enterprise AI, cloud, and engineering teams on policy and data classification
• Measure adoption, productivity, and quality using telemetry and report outcomes controlled by the platform
• Write architecture decision records for governance approval and mentor engineers across the platform organization

Requirements

• 10+ years of software engineering experience, including 5+ years building developer platforms or internal tooling at enterprise scale
• 2+ years designing and running LLM-based or agentic systems in production, including multi-agent orchestration (e.g., LangGraph)
• Experience with evaluation, cost control, failure handling, and human approval workflows for consequential actions
• Experience with knowledge graph or hybrid graph/vector retrieval design, ontology modeling, and data ingestion pipelines
• Working knowledge of Model Context Protocol, API design, event-driven integration, OAuth, and workload identity
• Familiarity with SDLC toolchain: Jira, Confluence, Git platforms, CI/CD, ServiceNow, OpenTelemetry
• Understanding of AI governance and security in regulated industries: data classification, prompt injection defenses, audit logging, least privilege
• Experience with developer portals (e.g., Backstage), InnerSource, rollout of coding agents, and/or measurement frameworks like DORA and SPACE

Benefits

• Great compensation package and bonus plan
• Medical, dental, vision, and matching 401(k)
• Flexible work environment (remote, hybrid, or in-office)
• Flexible time off including volunteer time off, vacation, sick time, and 12 paid holidays