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Senior Staff Machine Learning Engineer, Agentic Systems - Moveworks

Mountain View, California, United States

Actively hiring, first seen by us today
Pay
$201,300–352,300/year · BaseAnnual period assumed. Location-specific pay. Plus equity — pay source
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. Additional Information
Read the full posting
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Build the agent orchestration engine that manages long-running agent sessions

  • Build distributed session management with lease-based ownership and crash recovery

  • Build event-driven message pipelines with SQS FIFO, Kafka, gRPC and Socket.IO streaming

  • Build structured concurrency in Python asyncio with fail-fast and graceful cancellation

  • Build observability with OpenTelemetry tracing across async boundaries

From the employer’s posting
Agent orchestration engine — A state machine that manages long-running agent sessions
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
Observability infrastructure — OpenTelemetry instrumentation, distributed trace context propagation across async boundaries

What you’ll bring

All qualifications

Core experience

  • 10+ years building production backend/infrastructure systems
  • Experience designing and operating systems that handle real traffic at scale
Qualification wording
10+ years building production backend/infrastructure systems
Experience designing and operating systems that handle real traffic at scale
Apply at ServiceNow

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 4, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 69.

From 4,284 similar postings that came down. Coming down is not always a hire.

ServiceNow is hiring

36 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • ML Engineer hiring is picking up
  • Takes jobs down quickly
  • 22% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • DynamoDB
  • Kafka
  • Redis
  • Go
Where the posting names them
- 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
- 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
- 10+ years building production backend/infrastructure systems - Strong in Python or Go (ideally both) - Experience designing and operating systems that handle real traffic at scale
- 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
- 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
- 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
- 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
- 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)

Your next step

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Has ServiceNow posted this job before?

Yes. We’ve followed 3 other Senior Staff Machine Learning Engineer, Agentic Systems - Moveworks jobs there since April 2026. 2 came down, usually after about 35 days. One is still up.

  1. Mountain ViewCame down after 61 days, first seen Apr 16
  2. Mountain ViewCame down after 8 days, first seen Aug 26
  3. Mountain ViewStill up after 62 days, first seen Sep 3
  4. This jobUp 1 day so far, first seen Nov 4

Large employers often post one title for several teams, so these can be separate openings.

Job description

View original posting ↗

Job Description

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

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:

  • 10+ 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

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.  

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.  

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. 

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Company Description

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.

 

Source details

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Pay
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. Additional Information
Location & working pattern

Mountain View, California, United States

Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer
Work authorization

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