Altimate AI is at the forefront of the AI-driven data revolution, solving one of the biggest pain points in modern enterprise analytics—an overwhelming volume of data work and a shortage of skilled data professionals to manage it. Our mission: Automate and accelerate data operations, allowing data teams to focus on driving business outcomes faster.
With our flagship product, DataPilot, and our pioneering DataMates technology, we’re leading the charge in “agentic AI” for data teams. Think of this as virtual teammates embedded inside popular workflows —like the VSCode extension loved by thousands across 50+ countries—taking care of everything from data documentation to performance optimization. Users have given raving reviews about how it’s “an essential tool” and “game-changing for their data workflows.” This extension is just the tip of the iceberg, a tangible example of how we integrate seamlessly into tools teams already use. Fortune 1000 companies are our paying customers, and 100s of enterprise companies are active users of our free product offering.
Backed by top-tier investors and guided by Silicon Valley veterans who have scaled companies from startup to IPO, we have the vision, resources, and momentum to reshape how data teams operate.
Read more about us:
VentureBeat: How agentic AI could improve enterprise data operations
What Users Are Saying About Our VSCode Extension (one of many powerful tools in our platform)
As customer requests are pouring in for additional functionality with datamates, we are expanding our product team to take our Datamates platform to the next level. You will help expand and scale the capabilities of the DataPilot platform by envisioning, scoping, and launching next-gen functionality.
What makes this opportunity special:
Native GenAI product management experience: The industry is dividing into two camps: those who've built native GenAI products and those who've merely added GenAI features to existing products. Which camp do you want to be in?
First row seat in early-stage rocket ship: We are experiencing rapid growth that will explode in 2026, leading to experience and skills growth that only an early-stage high growth startup like ours can offer.
Direct collaboration with founders: Become an integral part of our decision-making process, working directly with founders to shape both engineering initiatives and go-to-market strategies.
Accelerated career trajectory: Join as a product manager at an early stage. As we scale, you can lead a team, shape strategy, and influence the entire industry.
What you'll do:
Own end-to-end quality across our front-end and Python backend (FastAPI, PostgreSQL, ClickHouse), serving multiple enterprise tenants
Create and manage test plans, test cases, and regression coverage for new features and releases
Review and steer AI-generated test suites — separating tests that catch real bugs from tests that just pass
Triage production issues and drive them to root cause
Develop and maintain QA tools and frameworks that support our automated testing pipeline
Run exploratory, usability, and manual testing where automation isn't the right tool
Collaborate with engineering and product to define test strategy across the development lifecycle
Must-haves:
Strong SQL — PostgreSQL plus an analytical database (ClickHouse or similar)
3 to 5 years of experience
Python with pytest — writing, reviewing, and debugging automated tests
API and backend testing depth — auth, multi-tenancy, error paths, not just happy-path 200s
End-to-end testing experience across front-end and back-end
Test plan, test case, and regression coverage ownership
AI-assisted quality engineering — using GenAI tools (Claude, ChatGPT, Copilot, Cursor) for test design and generation, and critically reviewing AI-generated tests and root-cause analyses
CI/CD integration experience — GitHub Actions or similar
Ability to read code and stack traces and trace a failure to its root cause
Clear, evidence-based bug reports and strong communication; self-motivated and able to work independently
Good to have:
Data pipeline and data testing understanding (dbt, warehouse concepts)
Snowflake or Databricks domain exposure — cost/performance optimization is our core domain
Experience evaluating LLM output (evals, golden datasets, quality rubrics)
Strong exploratory and usability testing craft
Load testing (Locust/k6) or security testing exposure
Front-end automation frameworks (Playwright, Cypress)
