Product Engineer

Fibr AI; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Fibr AI seeks a senior backend engineer to shape architecture and own the most complex parts of the platform. You will work directly with the founding team and influence technical direction from day one.

You will drive durable workflows, eval infrastructure, and production readiness for AI-powered features, partnering with a small, high-ownership team in Bengaluru. You’ll mentor peers and raise the bar across engineering.)

Qualifications

• 2-3 years of production backend experience.
• Python is your primary language and we move fast.
• Has shipped LLM-powered features to real users at scale, not demos.
• Has designed and owned eval infrastructure for LLM systems; show harnesses and data used for decisions.
• Has taken systems from 1 to 100, dealing with scale, reliability and incidents.

Responsibilities

• Own the hardest engineering problems: durable workflows, eval infrastructure, and agent reliability at scale.
• Set the technical direction for new surface areas like agent architectures and data models.
• Ship AI-powered features end-to-end and maintain high quality across the team.
• Design systems that survive rate limits, partial failures, flaky APIs, and real production load.
• Build the evals, guardrails, and instrumentation framework the team uses to ship.

Skills

Production backend

Python

LLM features

Eval infrastructure

System design

Incident handling

Durable workflows

Temporal/Celery

Tools

LangSmith

Langfuse

Prometheus

Job description

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 be a senior technical voice on the team shaping architecture, making the hard calls on system design, and owning the most complex parts of the platform. You'll work directly with the founding team and have real influence over where the product goes technically.

What you'll do

• Own the hardest engineering problems durable workflows, eval infrastructure, agent reliability at scale


• Set the technical direction for new surface areas agent architectures, data models, integration patterns


• Ship AI-powered features end-to-end and hold the bar for quality across the team


• Design systems that survive rate limits, partial failures, flaky third-party APIs, and real production load


• Build the evals, guardrails, and instrumentation framework the whole team ships against


• Sit at the table for architecture decisions and drive them forward


• Mentor and raise the bar for the broader engineering team

Must-haves

• 2-3 years of production backend experience


• Python is your primary language and we move fast


• Has shipped LLM-powered features to real users at scale not demos, not side projects. Talk about what broke, how you debugged it, and what you rebuilt


• Has designed and owned eval infrastructure for LLM systems show us the harness, the dataset, and how it drove ship/no-ship decisions


• Has taken systems from 1 to 100 not just 0 to 1. You've dealt with scale, reliability, and production incidents firsthand


• Deep experience with durable workflow systems in production Temporal, Celery, or similar at real scale


• Strong system design fundamentals you think about failure modes before you write the first line


• Strong product thinking alongside engineering depth you catch the product gap before the PM does


• Asks clarifying questions before jumping into solutions you understand the problem before you build the solution


• High ownership decisions are yours to make, not wait for

Nice-to-haves

• Multi-agent architectures or complex tool-use pipelines in production


• Experience with rate-limited third-party APIs at scale ad platforms, CRMs, analytics tools


• Vector stores, RAG pipelines, or retrieval systems in production


• LLM observability and tracing LangSmith, Langfuse, Prometheus, or similar


• Time spent as a founding engineer or early engineer at a seed/Series A startup


• Has mentored junior engineers or led technical decisions in a small team


• Strong product sense you catch the system design issue and the UX issue

This role is not for you if:

• Your AI experience is limited to personal projects or hackathons


• You've only built demos or PoCs that never reached real users


• You need detailed specs before you can start building


• You've only ever worked at large companies where someone else made the hard calls

How we work

High ownership, low bureaucracy. Decisions in the room, not in docs. You'll work directly with the founding team and have real influence over technical direction from day one.

Why Fibr AI

• Direct technical influence at an Accel-backed AI startup


• A chance to architect systems at the frontier of agentic AI