| Location | Mountain View, CA |
Were 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 youll 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
Qualifications
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