Lead AI Engineer

About Vahan

AI recruiter for India's massive blue-collar workforce

Tech

We're building technology to enable a fully-automated conversational experience in informal Indian languages such as "Hinglish". We are also using machine learning to build a reputation model for our users based on the data we collect from and from our employer partners. Our stack includes NodeJS, Python, RabbitMQ and Postgres.

The role

**Role title:** AI Engineer III**Location:** Bengaluru (On-site)**Experience:** 5+ years**About Vahan**\Vahan is a marketplace for blue-collar work. Zomato, Zepto, Swiggy and others hire through us; hundreds of recruitment agencies source through us. Samvaadini, our hybrid voice and WhatsApp agent, places 100,000+ outbound calls a day to people looking for delivery and warehouse work across 900+ Indian cities — qualifying them, answering questions about pay and shift timings, and handing the serious ones to a recruiter. It speaks Hindi, Hinglish, and a widening set of regional languages, mostly to people on low-end Android phones in noisy streets, many of whom have never used a chatbot before. When Samvaadini gets better, more people get placed in a job this week instead of next month.**The Role**\You'll own outcomes across the system, not one component — the voice and WhatsApp agents, the eval suite, the conversion funnel they feed, and root-cause analysis across code, agent behaviour, models, and data. At this level you'll more often be handed a number that moved than a task to complete: qualified handoffs down 12%? You localize it across code, agent behaviour, a silent model change, upstream data, or a market shift, then argue for the fix with the most leverage.**What You'll Do*** Own the outcome, not the ticket — investigate metric moves end to end and argue for the highest-leverage fix (sometimes that's doing nothing)* Know the funnel cold: outreach, connect, qualify, handoff, interview, placement — write your own queries* Own agent behaviour end to end: the loop, tool surface, context management, stop conditions, retries, and timeout handling* Build and defend the eval suite — every behaviour change ships behind a golden set and a regression gate* Fight for latency and cost — time-to-first-audio and inference cost at 100K calls/day are yours to defend* Work the voice pipeline — streaming ASR on code-switched Hinglish, turn detection, barge-in, graceful failure on network drops* Debug production non-determinism — reproduce rare failures, write postmortems, close the loop with evals* Use coding agents hard and well — Claude Code from Day 1**What We're Looking For*** Shipped an LLM-backed system in production, with real users, long enough for it to break* Can trace a business metric to its root cause across any layer — as comfortable in a warehouse query as a stack trace* Strong async Python — you write services, not notebooks* Brings up evaluation before we do* Model-choice opinions grounded in latency and cost — and you change them when shown better numbers* Fluent with coding agents; can name the last time one confidently produced something wrong and how you caught it* Can explain a technical trade-off to a recruiter or ops lead without dumbing it down* Learns fast in public**Nice to Have (Genuinely Not Required)**\Real-time voice stacks (LiveKit, Pipecat, Deepgram, ElevenLabs, Cartesia, telephony); Hindi/Hinglish or code-switched NLP; fine-tuning/distillation; durable workflow orchestration; ClickHouse or comparable analytical SQL; open-source work or public writing; MCP server authoring.

Skills

• Python
• LLMs
• RAG
• Fine-tuning
• AI Agents