It's fun to work in a company where people truly BELIEVE in what they are doing

We're committed to bringing passion and customer focus to the business.

The role
Cogentiq I2C is Fractal’s agentic AI Product for invoice-to-cash, covering Collections, Cash Application, Deductions, Invoice Management and Credit Risk. It runs on a Next.js front end, a FastAPI service layer, the Cogentiq agentic runtime, and a data tier on Azure Databricks with PostgreSQL.

You own the AI side: the agents, the models and everything that makes them accurate and dependable in front of a finance team. You design it, you lead the team that builds it, and you write code yourself.

What you will own
Technical design of the AI side: agent decomposition, orchestration patterns, tool design, memory and context strategy.
The agents across all five modules, from document extraction and matching through to the reasoning steps behind a recommendation.
Accuracy and reliability. Evaluation sets, regression suites, and a defensible number for how well each agent performs before it ships.




Guardrails and human oversight: confidence thresholds, escalation to a person, audit trails, and traceable reasoning for any decision touching cash.
Predictive and machine learning models where they serve the product better than an agent does.
Model strategy: choice of models, cost and latency per workflow, and the ability to switch providers without a rewrite.
The interfaces between your side and the platform, agreed jointly with the engineering.

How you will work
Lead the AI and agent engineering team. Set standards, coach engineers, and keep the team unblocked.
Stay in the code. Take the hardest agents yourself and set the patterns others follow.
Work as a pair with the Engineering Lead.
Work with product management on what an agent can realistically be trusted to do, so external commitments are grounded.
Be able to explain an agent’s behaviour to a finance stakeholder who will not accept "t

📌 Lead Ai Product Engineer Bengaluru
🏢 Fractal
📍 Bengaluru