At Drata, we're building a mindset. Everything we do springs from a high-velocity culture paired with a thoughtful hybrid model. This team is responsible for the in-product analytics and reporting experience our customers rely on to understand their compliance posture, surface insights from their Drata environment, and turn data into action.
This is a player-coach role. You will be writing code, designing systems, and shipping production AI features alongside a tight group of engineers, while also setting direction, unblocking the team, and growing into the leadership role. It is a great fit for a strong AI engineer who is ready to take their first formal step into management without giving up the keyboard.
The most important thing you bring is a real AI engineering background. You have shipped agents to production, you know what evals are and have built them, and you have strong data fundamentals to back it up.
What you'll do:
Build alongside the team by writing code, designing systems, and reviewing PRs
Own critical paths and pair with engineers on the hardest parts of the product
Keep close to the codebase and the customer experience even as the team grows
Set the bar for engineering quality through your own work
Lead a small team of engineers and grow it thoughtfully over time
Set clear goals, run good 1:1s, and create an environment where engineers do their best work
Give direct, useful feedback and help engineers grow in their careers
Invest in the basics of management: hiring, performance, career growth, and team health
Partner with leadership to grow into the formal management craft
Own the AI and data direction by setting the technical direction for AI-driven analytics and the data foundation underneath it
Make pragmatic decisions across the stack, from data modeling to agent design
Define multi-tenant data access patterns that safely serve customer-scoped data at scale
Make sound build, buy, and adopt decisions for the team's tooling
Stay current on developments in applied AI and bring relevant ideas back to the team
Build natural language data experiences by helping shape and build features that let users ask questions of their data in natural language
Ground AI responses in real data, handle ambiguity, and surface uncertainty appropriately
Keep AI-driven experiences fast, accurate, and trustworthy
Iterate quickly with design partners to find what works in production
Make evals a first-class practice by building the evals, telemetry, and offline/online test loops the team relies on
Establish eval-driven development as the default workflow
Define what "good" means for each AI feature and measure it rigorously
Use eval results to guide model, prompt, and architecture decisions
Ship and learn by driving end-to-end delivery from spec to GA
Partner with product on scope, sequencing, and tradeoffs
Ship iteratively to design partners, instrument adoption, and learn from real usage
Establish the metrics that prove the experience is delivering value
What you'll bring:
AI Engineering : Real AI engineering background with at least one agent or LLM-powered system shipped to production end-to-end
Working knowledge of prompts, tool use, retrieval, and structured outputs
Understanding of latency, cost, and quality tradeoffs in LLM-based systems
Familiarity with the failure modes of AI features in the real world
Evals : Hands-on experience designing and building evals for AI systems
Comfort with offline benchmarks, regression testing for non-deterministic systems, and online feedback loops
Ability to articulate how to evaluate an agent before, during, and after launch
Bias toward measurable quality over vibes
Data Fundamentals : Strong SQL skills and comfort with modern data warehouses
Experience with data modeling and the plumbing that powers analytics
Ability to reason about query performance, data contracts, and multi-tenant access patterns
Comfort working close to the data, not just on top of it
Hands-On and Pragmatic : Happy writing code and intend to keep doing it
Pragmatic about technology choices and careful about complexity
Bias toward shipping and learning over over-engineering
Comfortable working across the full stack on a small team
Ready to Lead : Track record of leading projects, mentoring engineers, and driving technical direction
Strong written and verbal communication
Direct, kind feedback style and a desire to invest in growing a team
Clear pull toward leadership, even without prior formal management experience
Requirements:
6+ years of software engineering experience, with at least 2 focused on AI/ML or applied AI work (agents, LLMs, evals, or similar)
At least one agent or LLM-powered system deployed to production that you owned end-to-end
Hands-on experience building and using evals to measure and improve AI quality
Solid data engineering or analytics engineering experience, including SQL, modeling, and modern data warehouses
Track record of shipping production software on small teams and operating across the full stack
Experience as a tech lead, project lead, or strong mentor, with a desire to grow into formal management
Strong written and verbal communication
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience
Bonus Qualifications :
Prior experience working on a customer-facing data product, embedded analytics, BI tooling, or a natural language interface over structured data (text-to-SQL, conversational analytics, or similar)
Experience with semantic modeling layers or modern BI infrastructure
Experience integrating AI agents with structured data sources
Background in compliance, security, GRC, or other regulated SaaS verticals
Prior tech lead or team lead experience
Previous experience at high-growth SaaS companies
How we support you:
At Drata, our people are our strongest advantageand 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.
Shared Success : We provide stock equity to ensure that as the company grows, you share directly in that success. Equity gives every employee a sense of ownership and the opportunity to celebrate our wins togetherbecause your contributions don't just support our progress; they help drive our collective success.
Health & Wellness:
Up to 100% employer-paid premiums for medical, dental, and vision coverage for employees and their dependents, along with comprehensive wellness benefits and healthcare concierge services designed to support your needs beyond traditional insurance.
Financial Well-being:
A comprehensive suite of financial benefits, including a 401(k) plan, company-paid life and disability insurance, tax-advantaged spending accounts, and a range of discounted voluntary offerings to help you customize and strengthen your overall financial position.
Family Support:
We want to support you in life's most important moments, so we offer a paid Parental Leave policy, after six months of employment. Employees also receive access to Kindbody fertility and family-building benefits and dedicated leave specialists who help guide you through the entire process.
Growth & Development: