ApplySarthi

Product Engineer

Fibr AI

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9,703 open product roles across 1,260 companies are on ApplySarthi right now, most of them in Bengaluru (354), Hyderabad (101), Delhi NCR (70).

What product roles keep asking for: Product management (49%), Stakeholder management (17%), SaaS (13%), Agile (13%) — counted across their open postings here.

Product Engineer jobs in Bengaluru · Product Engineer jobs in India · Remote Product Engineer jobs · FastAPI jobs · LLMs jobs · MongoDB jobs · PostgreSQL jobs

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Preparing for this interview

Interviews for product roles keep coming back to Product management, Stakeholder management, SaaS, Agile. Practise those questions before you sit with Fibr AI.

Questions you are likely to be asked

  1. Why do you want to join Fibr AI?
  2. What is your experience with LLMs? Tell me one thing you learned the hard way.
  3. How would you design an API for a feature you have worked on?
  4. What do you do when a production issue happens on your code?
  5. Walk me through a system you built. How was it designed, and what would you change now?

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**Product Engineer | Fibr.ai** Bengaluru · In office · 2-5 years Stack: Python · FastAPI · Temporal · PostgreSQL · MongoDB **The role** Fibr is building the agentic web experience layer - turning every URL into an intelligent agent that senses intent, makes decisions, and adapts in real time. Our agents personalise the full journey, running long LLM workflows against live customer accounts and millions of sessions. You'll own features end-to-end - from the rough idea in a Slack thread to something shipped, instrumented, and behaving correctly in production. New surface areas land on your plate every few weeks: a new agent, a new integration, a new optimization loop. You're responsible for the whole thing, including the evals and metrics that prove it works. You'll work directly with the founding team and ship to real users every week. **What you'll do** Ship AI-powered features end-to-end - backend, data, LLM layer, and the surface the user sees Design long-running workflows that hold up against rate limits, partial failures, and noisy third-party APIs Build and maintain the evals, guardrails, and instrumentation that decide whether a feature is good enough to ship Model the data behind agents and the analytics behind product decisions Sit in on architecture calls and shape where the platform goes next **Must-haves** 2-5 years of production backend experience Has shipped LLM-powered features to real users in production - not demos, not side projects. Be ready to talk about what broke and how you fixed it Has built and run evals for LLM systems. Show us the harness, the dataset, and the decisions it drove Comfortable across relational and document databases Has worked with a durable workflow or queue system in production Ships fast without breaking the build Nice-to-haves RAG, vector stores, or tool-use / multi-step agents in production Experience with rate-limited third-party APIs at scale (ad platforms, CRMs, analytics) Strong product sense - you catch the UX issue before the user does Time spent at an early-stage startup **How we work** High ownership, low bureaucracy. Decisions in the room, not in docs. You'll work directly with the founding team. **Why Fibr AI** Competitive salary + meaningful early-stage equity A chance to build deep expertise at the frontier of AI product development

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Listed on wellfound · posted 2026-10-12. ApplySarthi collects openings and links to application pages; the role is advertised by Fibr AI, not by us.