ServiceNow: Senior Staff Software Engineer, Agentic Systems - Moveworks — Mountain View, CALIFORNIA, United States

About ServiceNow

ServiceNow develops an enterprise software platform bringing together data, workflows and AI for business operations. Its employer introduction traces the business to automating a repetitive workplace task and describes a continuing focus on freeing people from routine work. The platform is intended to connect technology with how organisations carry out their processes. This makes workflow automation and the use of information in everyday business activity central themes, rather than a product aimed at only one industry.

The position and its setting

ServiceNow lists Senior Staff Software Engineer, Agentic Systems - Moveworks in Mountain View, CALIFORNIA, United States, under reference JB0076259. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Employment type: Full-time
• Employer listing date: 22 October 2026
• Brands: ServiceNow

Responsibilities and work described

• 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

Essential requirements and candidate background

• 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:
• 10+ years building production backend/infrastructure systems
• 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
• For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits
• Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure
• Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies and work location
• We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Work arrangement: On-site
• Advertised location: Mountain View, CALIFORNIA, United States

Benefits mentioned by the employer

• 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

Employer details to confirm

• The employer’s seniority category and its stated experience requirements do not agree. Follow the role-specific requirements above rather than assuming this is a fresher opening.

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Senior Staff Software Engineer, Agentic Systems - Moveworks vacancy is not an offer for reference JB0076259; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to ServiceNow

Applications follow the official employer page linked below.

Open the official ServiceNow posting below and match the title and reference JB0076259.

Compare your qualifications and experience with the essential conditions for the Mountain View, CALIFORNIA, United States position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• Kafka
• AI/ML
• AI
• sales