Senior QA Engineer

Altimate AI; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Altimate AI in Bengaluru is expanding its QA team to scale the Datamates platform, envisioning new testing capabilities and ensuring product reliability across tenants.

You will own end-to-end QA for the frontend and Python backend, create test plans, review AI-generated tests, and collaborate with engineers to drive quality from development through release.

Qualifications

• Strong SQL skills with PostgreSQL and/or ClickHouse.
• 3–5 years of testing experience in backend/frontend/API.
• Python with pytest for automated tests.
• API and backend testing including auth and multi-tenancy.
• End-to-end testing across frontend and backend.
• Ownership of test plans and regression coverage.
• Experience using GenAI tools for test design and generation.
• CI/CD integration with GitHub Actions.
• Ability to read code and trace failures to root cause.
• Clear bug reports and strong communication.

Responsibilities

• Own end-to-end QA across frontend and Python backend (FastAPI, PostgreSQL, ClickHouse).
• Create and manage test plans, test cases, and regression coverage for new features and releases.
• Review and steer AI-generated test suites and ensure they catch real bugs.
• Triage production issues and drive root-cause analysis.
• Develop and maintain QA tools and frameworks for automated testing pipelines.
• Run exploratory, usability, and manual testing where automation isn’t ideal.
• Collaborate with engineering and product to define test strategy across the development lifecycle.

Skills

SQL (PostgreSQL)

ClickHouse

Python with pytest

API testing

End-to-end testing

Test planning

GenAI QA

CI/CD (GitHub Actions)

Debugging

Communication

Tools

Playwright

Cypress

Locust

Job description

Why Join Us

Automate and accelerate data operations, allowing data teams to focus on driving business outcomes faster. With our flagship product,

Why Join Us

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)

Your Impact

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)