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Member Of Technical Staff – Agent Orchestration

Anuvaya Labs · anuvaya.com
New DelhiOn-siteLead / Manager
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The job in short

A lead / manager full-time on-site Machine Learning / AI Engineer role at Anuvaya Labs in New Delhi. Skills mentioned: Kafka, LLM.

KafkaLLM

Details

Found
39 d ago · posted 2026-07-14
Location
New Delhi

Full description

About Anuvaya We think conversational AI agents will deliver all professional services in India. We started with astrology. We're a small group of engineers, designers, and product folks building at the intersection of conversational AI and domain expertise. Making an AI agent sound human-like is hard. Making an AI an expert in a domain is also hard. We're doing both together. We're backed by Accel, Arkam Ventures, and Weekend Fund. The Role Most AI agents treat conversations as stateless request-response cycles. Ours doesn't. We've built a stateful agent that streams responses with natural pacing, handles mid-response interruptions without corrupting state, decides autonomously whether to keep talking or wait, and maintains a living context that evolves across turns. The Agent Orchestration team owns the core runtime - the system that coordinates LLM calls, tool execution, context management, delivery pacing, and conversation persistence. When you break something here, users notice in real-time. When you get it right, the agent feels like talking to a person who genuinely knows what they're doing. What You'll Do • Own and evolve the stateful agent runtime - the streaming pipeline, state management, and tool execution layer • Ensure what the user sees, what the model remembers, and what we persist stay perfectly in sync - even when users interrupt mid-response • Build and refine the streaming architecture - how responses are buffered, delivered, and recovered cleanly on interruption • Implement and tune delivery pacing - making the agent's output feel natural, not robotic • Design the tool execution layer - the agent calls domain-specific tools mid-conversation and reasons over results in real-time • Work on autonomous continuation - the agent deciding when to keep going and when to stop, based on conversational context • Optimize for latency and reliability - first-token time, interruption recovery, context window management What We're Looking For • Deep systems programming instincts - you think about state machines, concurrency, race conditions, and failure modes naturally • Experience building real-time or streaming systems - WebSockets, SSE, or similar • You've built and maintained stateful, long-running processes in production • Comfort with distributed systems - message queues, event-driven architectures, service coordination • Strong debugging skills for systems where "it worked on my machine" is never the problem • You can read and reason about concurrent code - whether it's Elixir processes, Go goroutines, or async runtimes Bonus • Experience with Elixir/OTP - GenServers, supervisors, the actor model • Familiarity with LLM APIs and streaming protocols (SSE, chunked responses) • You've built or worked on conversational AI systems (not just chatbot wrappers) • Experience with NATS, Kafka, or other messaging systems • You've read our whitepaper on Stateful Agent Orchestration and can poke holes in it How We Work We care about craft obsessively. Your work gets questioned, pulled apart, and rebuilt - not because we're harsh, but because everyone here holds each other to a standard most places don't bother with. We work out of a hacker house in Vasant Kunj. We strongly encourage everyone to be in office. If that sounds like the only way you'd want to work - let's talk.

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