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Open nowPosted 49 days ago

AI Product Engineer

Coditude12 open roles

Where
Pune
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Your applicationOpen nowAI Product EngineerCoditude · Pune

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Early applications get read.

15.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 6.5%3 days
  3. 15.1%7 days
This job: posted 49 days ago

The posting

Must-Have Skills:

  • Strong software engineering fundamentals in at least one stack — clean APIs, sensible data models, tests, real debugging. Depth in one stack beats familiarity with five.
  • Learning agility — a provable track record of entering an unfamiliar domain or codebase and shipping within weeks. This can substitute for most stack requirements.
  • AI-native development with judgment — uses Claude Code or equivalent agentic tools as a primary way of building. Should be able to drive one live in the interview and explain where they took the keyboard back.
  • High agency and builder's bias — takes an ambiguous ask and drives it to a shipped, measured fix.
  • PostgreSQL competence — real queries, indexes, transactions, and the instinct that a wrong query is a customer-visible bug.
  • Clear communication — can explain trade-offs to non-engineers without jargon, writes clearly, and is comfortable with real client contact.
  • Working understanding of LLM agents — should be able to speak to what they've built with an LLM API and how it failed on them. Production-level depth is not required; we teach that.

Good-to-Have Skills:

Our environment (depth in some is a plus; candidate ramps on the rest):

  • Python 3.11 (FastAPI, asyncio, pydantic)
  • Anthropic and OpenAI SDKs
  • Next.js / React / TypeScript at working proficiency
  • Redis, Typesense
  • AWS (EC2/ALB, RDS, SQS, SES)
  • GitHub Actions, Datadog

Genuine bonus:

  • Production LLM/agent work (evals, guardrails, multi-agent, MCP)
  • Prior forward-deployed or consulting-style client work
  • Airflow or data pipelines
  • Browser automation, OCR/vision

Roles & Responsibilities:

  • Build and operate AI agents and LLM-powered products — copilots, workflow agents, extraction pipelines, internal tools — and maintain/evolve existing ones.
  • Own problems end to end: from the client conversation through design, code, deploy, and production support.
  • Work AI-first, with humans owning judgment and outcomes — validate what the tools produce and own every line that ships.
  • Take part in client and partner conversations: discovery, live demos of work in progress, pilot support.
  • Write short proposals and design docs; decisions move through documents and PRs, not meeting chains.
  • Run a lane end to end within a small, async-first team.
  • Write tests where they protect what matters — agent behaviour and money paths. No coverage theatre.
  • Apply AI security basics: prompt injection via untrusted content, least-privilege tool permissions, secrets hygiene, verifying anything inbound before acting on it.
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