Senior Platform AI Engineer
Описание вакансии
At Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.
We live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.
Our Culture & Work Style 🚀
At Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:
We pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.
If you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.
Why Join The Drata Team?
The best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.
Drata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand, deployment pipelines that handle model upgrades without breaking output quality, and orchestration layers that manage multi-step agent workflows with persistent state.
This is not a traditional infrastructure role. You'll debug prompt templates alongside Terraform modules. You'll design API schemas optimized for LLM token budgets, not just HTTP throughput. When a model upgrade changes behavior across 15 workflows, you'll assess quality impact — not just confirm the containers are healthy.
You'll work closely with our agent developers, product engineers, and an embedded SRE partner, sitting at the intersection of AI development and production reliability.
Our north star is simple: minimize the time it takes to launch a new agent in production. You're someone who asks "are we solving the right problem?" before writing the first line of code, who builds systems that make five other engineers faster, not just yourself, and who's equally proud of what they chose not to build.
MCP SERVER DEVELOPMENT & AI-OPTIMIZED API DESIGN
AGENT ORCHESTRATION & WORKFLOW INFRASTRUCTURE
LLM OPERATIONS & MODEL LIFECYCLE MANAGEMENT
PRODUCTION AI INFRASTRUCTURE & RAG SYSTEMS
PLATFORM ENABLEMENT & DEVELOPER EXPERIENCE
7+ years of software engineering experience, with 2+ years building or operating AI/ML infrastructure in production. You're strong in Python (our AI services are built in Python), with TypeScript/Node.js a nice-to-have. You've worked with LLM APIs, vector databases, or AI orchestration platforms and understand the difference between "the service is up" and "the model output is good." You're comfortable across the stack: writing Terraform one day, debugging a prompt template the next, and designing an agent orchestration framework the day after.
Specifically, you bring experience in several of these areas: cloud infrastructure (AWS preferred — ECS, S3, Bedrock), container orchestration, infrastructure-as-code, CI/CD pipeline design, API design, workflow orchestration engines, and distributed systems. You've worked with at least some AI-specific tooling: LLM APIs (Claude, OpenAI, etc), model serving frameworks (vLLM, SageMaker etc), vector databases, embedding pipelines, prompt management platforms, or agent frameworks.
You communicate clearly about technical tradeoffs, especially when explaining AI-specific infrastructure decisions to stakeholders who think in terms of traditional reliability engineering. You own what you see broken, not just what's assigned to you, and you can spot when an architecture decision will fail at scale and say so early, clearly, and with an alternative.
At Drata, our people are our strongest advantage—and we prove it with support that exceeds industry standards. Our total rewards package is designed to power your well-being, accelerate your growth, and keep your work-life balance thriving.
Explore how we invest in your Life at Drata https://drata.com/about/life-at-drata?utm_source=chatgpt.com.
This role will receive a competitive base salary, benefits, and stock, typically in the form of Restricted Stock Units (RSUs). The applicable salary range for this role is: $192,000 - $259,800.
A variety of factors are considered when determining someone’s leveling and compensation–including a candidate’s professional background and experience. These ranges may be modified in the future and final offer amounts may vary from the amounts listed above.