Original listing text, shown exactly as published by the company.
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.
