Staff Software Engineer, Agentic Systems - Moveworks

The Role
We're building the runtime infrastructure that powers Moveworks' AI agents — the systems that orchestrate, execute, and deliver agent responses to millions of enterprise users in real time. This is not an ML role. This is a distributed systems engineering role at the heart of the agentic AI wave.
Our AI agents can plan, execute multi-step workflows, call tools, wait on human input, and resume — all while maintaining correctness, observability, and low latency. The systems that make this possible are what you'll build and own.
What you get to do in this role:
Agent orchestration engine — A state machine that manages long-running agent sessions, coordinating planning, execution, and user interaction across multiple LLM calls and tool invocations
Distributed session management — Lease-based ownership using DynamoDB conditional writes, heartbeat protocols, and crash recovery via checkpointing
Event-driven message pipeline — SQS FIFO queues for ordered delivery, Kafka consumers for event processing, and real-time streaming via gRPC and Socket.IO
Structured concurrency — Python asyncio TaskGroups running multiple concurrent tasks per session (message polling, lease heartbeats, output publishing, orchestrator execution) with fail-fast semantics and graceful cancellation
Observability infrastructure — OpenTelemetry instrumentation, distributed trace context propagation across async boundaries, custom span lifecycle management for sessions that span minutes
Caching and state layers — Redis, DynamoDB KV stores with per-org/per-bot scoping, batch read optimization, and hot-reload configuration
To be successful in this role you have:
You should have deep experience in at least 3 of these areas:
Distributed systems: consistency models, idempotency, exactly-once delivery, distributed locking/leasing
Concurrent/async programming: Python asyncio, Go goroutines, structured concurrency, cancellation handling
Event-driven architectures: message queues (SQS, Kafka), pub/sub, backpressure, delivery guarantees
Database systems for infrastructure: DynamoDB (conditional writes, transactions), Redis (connection pooling, pub/sub)
Observability: OpenTelemetry, distributed tracing, span context propagation, Prometheus metrics
gRPC/protobuf: streaming RPCs, service interface design, error handling patterns
Required:
7+ years building production backend/infrastructure systems
Strong in Python or Go (ideally both)
Experience designing and operating systems that handle real traffic at scale
Comfort with ambiguity — these are novel problems without textbook solutions

Employment type
Full-time

Work arrangement
No