Tetriz jobs, judged for you, free

What they do

Tetriz measures how engineering teams use AI coding tools such as Cursor, Claude Code, and GitHub Copilot. It connects AI coding sessions to pull requests, coaches engineers on prompts and workflow, and gives engineering leaders numbers for the return on AI. Workloom Solutions Private Limited owns the product.

What they value

• Building, over research: postings ask for shipped work, not papers.
• Breadth: engineers are asked to cross into product, frontend, and data.
• Using AI agents internally, which the marketing postings describe in detail.
• Evidence of initiative, such as a portfolio or a GitHub of real work.
• Working from the Bengaluru office, which the postings state.

Where they hire

Every one of the eleven postings is in Bangalore. Nine are on site, one is hybrid, and one is remote. The remote one is a founding go-to-market lead for North America, and it is still listed under Bangalore. No posting mentions sponsorship or the right to work.

Teams and roles

The board is small and the titles say the stage. Four of the eleven postings are internships.

• Engineering: two member of technical staff roles for core full stack and backend work, one of them senior, and one for DevOps and infrastructure.
• Data science: a DS/ML engineer who owns evaluation systems, model routing, and inference cost.
• Product: a GenAI product builder internship.
• Marketing: an associate product marketing manager and a product marketing internship, both running the content engine.
• Commercial: a founding go-to-market lead for North America and a go-to-market sales role for India.
• Internships: an AI engineering internship and a DS/ML internship.

What they look for

Postings ask for the work, not the years. The engineering roles ask you to build production AI agents and to wrap reliable software around model output that is not deterministic. The infrastructure role asks you to own cloud environments, orchestration, and CI/CD, and to lead a cloud migration. The DS/ML role asks for failure taxonomies, LLM-as-judge rubrics, golden datasets, and model routing. The marketing roles ask you to build a workflow for any repeated task, and say that a candidate who starts from a blank document will not enjoy the work. The internships say coursework alone is not a fit.