AI Product Engineer
Mumbai · Senior
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What we know about this role
LOW
Our tracked job listings for treelifeventures show limited recent activity.
First 72 hours
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Skills required
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Job description
- In-house AI products: architecture, upgrades, quality, and release until deployment
- Technical execution for AI development happening inside the company
- Software and hardware infrastructure the products run on (hosting, servers, environments, usage, cost, reliability)
- Product adoption from a technical side: rollout, stability, usability, and feedback into the next build
What will be your key responsibilities?
- Own development and upgrades from design through testing to production
- Work in the codebase: architecture, AI tooling, integrations, and release quality
- Definition of done is deployment. Code that is written but not live is not done
- Keep the product stable: fewer regressions, less leftover WIP, faster path from change to live
- Own the in-house AI product(s) as a builder: what we ship, how it is built, and whether it holds up in production
- Turn business problems into technical solutions, not a list of tickets for someone else
- Make build vs buy vs ignore calls on AI tools, models, and frameworks
- Stay hands-on with hosting, servers, environments, usage, and cost
- Size infra to the product. Reliability and spend are part of the job, not a side conversation
- Keep product decisions and server reality aligned
- Stay current on AI tools, models, frameworks, and how the market is moving
- Recommend what we should adopt, what we should skip, and what we should build ourselves
- Keep the stack current without chasing every new tool
- Treat adoption as a core outcome. A product that is live but unused has failed
- Support internal rollout with a product that is stable, fast, and easy to use in real workflows
- Measure usage and drop-off, then feed that back into what you build next
- Entrepreneurial mindset: ownership, speed, trade-offs, and whether this makes the business better
What are the key requirements for the role?
- 4-6yrs of strong technical base: architecture, APIs, data flow, models, and deployment. You can build, not only describe
- Hands-on with AI products and the current AI toolchain (LLMs, embeddings, agents, evaluation, orchestration)
- Working knowledge of software and hardware/infra: hosting, servers, environments, basic networking and usage
- Experience taking a product from build to live yourself, ideally an internal tool or AI product in a services / professional-firm environment
- Cloud hosting, cost optimisation, and production monitoring experience
- Product sense with a business lens: adoption, value, and cost, not only shipping features
- Entrepreneurial mindset: ownership, bias to action, comfort with incomplete information
- Clear communicator with engineers and with the business
- Comfort helping people move from old workflows onto a new product
- Mid-level: you can run this without being managed day to day
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