Manager, AI Engineering - Analytics

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from.

Why Join the Drata Team?

At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for:

Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go.

Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them.

A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level.

Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience.

A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates.

Job Summary:

We are seeking a hands-on engineering leader to head a new, small analytics engineering team at Drata. 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

Stay deeply hands-on 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

Lead a small, focused 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

Set 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

Help 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

Build 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

Drive 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 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.

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 together—because 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: Generous annual stipends for both professional and personal development, empowering you to invest in your continued growth. You’ll also have access to a wide range of internal learning opportunities, ensuring you can build new skills, deepen your expertise, and advance your career with confidence.

Time Off & Flexibility: We believe that to do your best work, you should get the time you need for rest, rejuvenation and recovery. Drata offers a flexible vacation policy, paid holidays, and other perks to recharge.

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: $197,800 - $267,600.

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.