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Member Of Technical Staff – Agent Orchestration

Anuvaya Labs·August 24, 2026·
🌍 Remote · RemoteFull-timeSoftware Engineering

💰 $80,000 – $130,000/yrMarket estimate · not provided by the employer

At a glance

Who can apply
Not stated by the employer
Work arrangement
Remote · Remote
Employment type
Full-time
Salary
$80,000 – $130,000/yr · market estimate

Checked against the employer's source on October 12, 2026. Details come from the employer's posting; confirm them on the application page.

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Job 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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