Senior Platform Engineer 2, AI Tooling

Drata • San Francisco, CA

3d • $174,500 - $236,100 • Hybrid

About The Position

The Senior Platform Engineer II, AI Tooling on the Developer Experience Team (part of Foundation Engineering group) will lead the design and delivery of the internal AI platform that makes Drata's engineers more efficient - the tools, agents, and integrations that turn AI coding agents (and the rest of the AI dev stack) into a paved road for everyday engineering work. This is not a product-AI role - you're not building AI features for Drata's customers. You're building for Drata's engineers: MCP servers that connect AI agents to our internal systems, custom agent skills and subagents tuned to how Drata works, agentic workflows that automate the engineering lifecycle end-to-end (code generation, verification, testing, delivery), and the governance, observability, and cost controls that keep all of it safe and accountable.
Your "customer" is not Drata's normal users, it's Drata's engineers. The work is measured upstream of every PR: shorter cycle time, less toil, fewer mistakes, faster onboarding, more time on the work that matters. You'll set technical direction, mentor engineers, and make the architecture calls that shape how AI shows up in every engineering workflow at Drata.

Requirements

• 7+ years of experience as a software engineer building production systems and platforms
• 1+ years of hands-on experience customizing or extending AI coding tools in a real engineering context: agent skills, subagents, hooks, plugins; agentic IDE rules and extensions; MCP servers; or similar
• Daily user of AI coding tools
• Deep working knowledge of MCP (Model Context Protocol): authoring servers, designing tool interfaces, scoping permissions, handling auth
• Strong working knowledge of the Anthropic API (preferred) or equivalents: tool use, structured outputs, prompt caching, batch API, streaming
• Solid prompt engineering experience for agentic workflows - not chatbot prompts, but multi-step engineering tasks with tools, verification, and recovery
• Track record of building agentic workflows that span the full coding lifecycle: planning, generation, verification, testing, and delivery
• Experience integrating AI into CI/CD pipelines: GitHub Actions, automated PR review bots, agentic test generation, background coding agents
• Strong backend and systems background: TypeScript, NodeJS, or Python in production, REST and event-driven architectures, CI/CD systems
• Comfort building developer-facing tooling: CLIs, GitHub Apps, internal portals
• Working understanding of the security and governance side of AI dev tools: code and data egress policies, secrets in prompts, prompt injection risk inside repos, audit trails for AI-driven changes
• Understanding of LLM cost and latency tradeoffs as they show up in dev workflows: token caching, batch jobs, async agents, model selection
• Strong skills in the Drata core stack: NodeJS, TypeScript, Temporal, MySQL, Git, REST
• Experience building in AWS
• Familiarity with engineering productivity measurement (DORA, DX, SPACE) and how to instrument it
• Strong opinions about developer experience and the "paved road" model: the right tool has to be the easy tool, or engineers will route around it
• Track record of owning ambiguous platform problems end-to-end and shipping them
• Comfortable making architecture calls under uncertainty in a space that changes monthly
• Experience mentoring engineers and unblocking other teams
• Outstanding ability to negotiate difficult tradeoffs (quality vs. speed, build vs. buy, mandate vs. paved road)
• Excellent written communication: design docs, RFCs, post-mortems

Nice To Haves

• Published agent skills, plugins, or open-source AI dev tool contributions
• GitHub App development at scale
• Terraform
• Self-directed, adaptable, and excellent problem-solving and analytical skills

Responsibilities

• Architect the internal AI platform: MCP servers, agent customizations, agentic workflows, engineering harness, and integrations that make AI the default way engineers get work done at Drata
• Design and ship custom agent skills, subagents, hooks, and plugins tuned to specific engineering workflows (code review, test generation, PR triage, on-call, release notes, migrations)
• Build end-to-end agentic workflows that automate code generation, verification, testing, and delivery: agents that pick up a ticket, write the code, run the tests, and ship the PR
• Design async, recoverable, long-running agent workflows - Temporal is already in our stack and is a natural substrate for agents that run for minutes or hours and have to survive restarts
• Lead the rollout and customization of AI coding tools across the org
• Wire AI into CI/CD: automated PR review, test generation, doc generation, migration agents, bug triage agents, autonomous coding agents in pipelines
• Build the governance layer: usage telemetry, cost tracking, audit trails, security policy enforcement (what code can leave the org boundary, secrets scrubbing, prompt injection defenses inside the repositories)
• Design and run evals that tell us which PR review prompts actually catch bugs, which skills produce useful output, which agents save time vs. cost time - and how we know in production
• Measure adoption and impact with engineering productivity frameworks and adjust the platform accordingly
• Partner with Security, Legal, and Compliance to keep AI usage inside Drata's customer-trust boundaries
• Mentor engineers, set technical direction, and review designs across the org
• Stay current with the AI coding tool landscape and bring back what's useful
• Participate in design and coding activities, write reusable and testable code, and deliver in an agile team environment
• Participate in design reviews, post-mortems, and on-call for the AI Tooling platform

Benefits

• Stock equity
• Up to 100% employer-paid premiums for medical, dental, and vision coverage for employees and their dependents
• Comprehensive wellness benefits and healthcare concierge services
• 401(k) plan
• Company-paid life and disability insurance
• Tax-advantaged spending accounts
• Range of discounted voluntary offerings
• Paid Parental Leave policy, after six months of employment
• Kindbody fertility and family-building benefits
• Dedicated leave specialists
• Generous annual stipends for both professional and personal development
• Wide range of internal learning opportunities
• Flexible vacation policy
• Paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed