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Salary
≈ $22k – $46k per year (Estimated)
Location
In office (Bengaluru)
Experience
8+ years exp

First seen by Alion on Sep 30, 2026.

Overview
Company
Impact
Profile match
Founded in 2016, Qrata is an innovative talent acquisition and curation platform specializing in cross-border hiring and workforce solutions for high-growth startups. Headquartered in Mumbai, India, the enterprise connects global companies with top-tier Indian talent through AI-driven matching, structured evaluations, and end-to-end recruitment services. By streamlining everything from candidate sourcing to local legal setup and payroll management, it enables international businesses to efficiently build and scale remote teams.

Who We Are :

The infrastructure layer that sits between shipping code and confident releases. We're not a test automation tool. We're the system that understands your application, learns from every test run, and tells engineering teams exactly what's at risk before anything breaks in production.

What This Role Is :

You will be one of the first engineers building the core agent layer of the platform. This is not a role for someone who chains LLM API calls and calls it agentic. The systems you'll build have deterministic rule layers, multi-stage reasoning pipelines, confidence scoring under ambiguity, feedback loops that improve over time, and escalation logic that knows when to stop and ask a human.

What You'll Build :

- Multi-agent orchestration systems : agents that plan, execute, self-correct, and escalate.

- Context Graph infrastructure : a living knowledge graph that connects requirements, DOM elements, test cases, code functions, and user behavior signals.

- Browser crawl agents : Playwright-based agents that understand a running application semantically.

- Agentic evaluation frameworks : building the eval layer to verify agent decisions.

- LLM integration at production scale : prompt engineering, structured output, context window management, and confidence calibration.

- Feedback loops : systems that get measurably smarter with every test run.

What You Need to Have Done Before :

- Built and shipped multi-agent systems in production.

- Worked with LangGraph, LangChain, CrewAI, AutoGen, or equivalent orchestration frameworks.

- Designed and queried knowledge graphs or graph databases (Neo4j).

- Built systems that detect absence : not just what's wrong, but what's missing.

- Written production Python (async, typed, modular, observable).

- Worked with Playwright, browser-use, or equivalent browser automation.

Backend Tech Stack :

Python (async, typed, strict), FastAPI, Celery, Redis.

How We'll Evaluate You :

Beyond the standard interview, we give candidates a take-home assignment that we think is the truest signal of the skills this role demands. You'll be asked to build a working agent that crawls a live web application, ingests a product requirements document, constructs a knowledge graph, and uses that graph to reason about the blast radius of a code change.

What We Offer :

- Competitive compensation benchmarked to top-of-market.

- Meaningful equity.

- Direct access to the founding team and genuine influence over product direction.

- The chance to be a core architect of a category-defining platform.

Skills

Python, LangChain, Neo4j, LangGraph, FastAPI, Playwright Testing, Artificial Intelligence, Agentic AI, LLM

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