Senior Staff Software Engineer, Agentic Systems - Moveworks

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

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.

Responsibilities

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

Requirements

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; 12+ 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