ServiceNow

Staff Machine Learning Engineer

ServiceNow • $176K — $308K *
Santa Clara, CA 95051In-Person
Information Technology
8 - 10 years of experience
Today
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Job Overview by Ladders

Qualifications

  • 8+ years in software development with significant LLM/agentic system experience.
  • Expertise in LangGraph and/or LangChain.
  • Strong understanding of MCP, ideally having built an MCP server.
  • Proficient in production async Python, especially FastAPI and WebSockets.
  • Experience making architecture decisions for agent systems, including tool boundaries and cost trade-offs.
  • Whole-stack capability, able to work across Python, Spring Boot, and React.
  • Comfort with ambiguity and setting technical direction.

Responsibilities

  • Design agentic systems focusing on state management and tool boundaries.
  • Develop and maintain the industry's leading agent execution runtime known as The Harness.
  • Integrate MCP with the evolving Harness for efficient agent interaction.
  • Implement A2A protocols for proficient agent-to-agent task delegation.
  • Participate in Forward Deployed Engineering to adapt solutions to customer workflows.
  • Manage RAG and context engineering for document ingestion and prompt design.
  • Engage with classical ML pipelines when applicable.

Benefits

  • Health plans including flexible spending accounts.
  • 401(k) Plan with company match.
  • Equity options where applicable.
  • Matching donations for various charitable causes.
  • Flexible time away and family leave programs.
Full Job Description
Job Description

Team Overview

We build the AI layer of our CPQ platform - a set of Python services that let users configure, quote, and manage transactions through natural language instead of forms. This isn't a thin LLM wrapper. We're running multiple production agent architectures concurrently (ReAct-style tool-calling agents, hand-rolled LangGraph state machines, and the Harness - our from-scratch, industry-leading agent execution runtime). Our systems are backed by a first-party MCP surface into admin/product/rules/transaction systems and interoperate with other AI agents over the A2A protocol. Below that sits a conventional Java/Spring Boot microservices fleet and a React/TypeScript + Lit frontend that the agents ultimately drive.

Role Overview

We're looking for someone who already operates at a Senior-Staff bar in the agentic/LLM domain but is building out breadth across the rest of the stack. You'll be one of the most senior technical voices on how agentic systems get designed here - state management, tool boundaries, streaming protocols, prompt/context architecture, and multi-agent coordination - while staying credible end-to-end: able to read a Spring Boot service, unblock a frontend integration, or reason about a classical ML model pipeline when the problem calls for it.

What you get in this role:
  • Multi-agent orchestration - LangGraph/LangChain agents over frontier LLMs for transaction editing, conversational configuration, and multi-product quote planning with plan/approve/refine loops and parallel task execution
  • The Harness - we're crystallizing our own agent execution runtime into an industry-leading, state-of-the-art harness. Full-duplex sessions where a user can interrupt, redirect, or answer a clarifying question mid-execution while other work keeps streaming, built on a from-scratch async runtime rather than a bolted-on wrapper around someone else's agent loop. This is as much a performance and UX problem as a backend one - low-latency streaming, backpressure, live progress, partial results, graceful cancellation - and it's the part of the stack we're most invested in owning outright. You'd be a primary owner of where this goes next.
  • MCP as a secondary interface - we maintain a first-party MCP server and clients into our admin/product/rules/transaction systems, but as the Harness matures it becomes the primary way our own agents interact with the platform, with MCP kept as the secondary, standards-based surface for external interop. You'd help decide what stays MCP-first and what moves onto the Harness.
  • A2A protocol - agent-to-agent task delegation and streaming, surfaced through an external gateway so other systems (including core ServiceNow) can drive our agents directly
  • Forward Deployed Engineering - expect real time embedded with customer- and product-facing teams against live deployments. Adapting the Harness and our agents to actual customer workflows under real constraints, not just building platform capability in the abstract
  • RAG / context engineering - tenant-uploaded document ingestion, categorization, and aggregation into agent context. Prefix-cacheable prompt design for cost/latency
  • Classical ML, when the problem isn't a good fit for an LLM - we have a separate PyTorch/scikit-learn training and serving pipeline (field-value prediction) that a whole-stack ML engineer should be able to read, extend, or evaluate against LLM-based alternatives
  • Full-stack fluency - enough comfort in Spring Boot/Java services and the React/TypeScript + Lit frontend to unblock an integration end-to-end without waiting on a handoff


Qualifications

To be successful in this role you have:
  • 8+ years building production software, with several years specifically shipping LLM-powered / agentic systems (not just API wrapper calls - real tool-use loops, state management, multi-turn orchestration)
  • Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
  • Deep, hands-on expertise with LangGraph and/or LangChain (or the judgment to know when to skip them and hand-roll something better)
  • Strong understanding of MCP - ideally having built an MCP server, not just consumed one
  • Production async Python (FastAPI, asyncio) - comfortable with WebSockets, streaming, and the failure modes of long-lived stateful connections
  • Track record of making real architecture decisions on agent systems - tool boundaries, context/state design, cost/latency tradeoffs, when a bounded agent beats a fully autonomous one
  • Enough range outside Python to read/modify a Spring Boot service and a React component without hand-holding - this is explicitly a whole-stack role, not "Python specialist with a frontend allergy"
  • Comfort operating with ambiguity and setting technical direction, not just executing a spec - this is a Staff-level bar on judgment
  • A demonstrated habit of pulling the latest from the industry - new agent frameworks, protocol standards, model capabilities - into production quickly
  • Willingness and ability to build real fluency in the Core ServiceNow platform. Our systems increasingly need to interoperate with it directly, and this role is expected to help drive that, not just react to it
  • Willingness to work directly with customers/deployments as part of Forward Deployed Engineering efforts - this isn't a purely internal-platform role

Desired Qualifications
  • Experience with classical ML (PyTorch/scikit-learn) in addition to LLM-based systems
  • Experience with A2A or other agent-to-agent interop protocols
  • Experience with RAG / knowledge-graph systems (embeddings, vector or graph-based retrieval)
  • Multi-tenant SaaS experience, especially around per-tenant isolation of stateful connections/resources
  • CPQ, quoting, or transaction/pricing domain experience
  • Prior Forward Deployed Engineering experience, or time spent embedded with customers shipping bespoke solutions exposure


For positions in this location, we offer a base pay of $176,100 - $308,200, 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. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

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.

About ServiceNow

ServiceNow provides cloud-based solutions that define, structure, manage, and automate services for enterprise operations in North America, Europe, the Middle East, Africa, the Asia Pacific, and other countries. The company offers service management solutions, including incident, problem, change, request, and cost management as well as service catalogs; and IT, HR, facilities, and field service management solutions. It also provides IT operations management solutions covering service mapping, delivery, and assurance solutions; business management solutions such as financial management, project portfolio suite, vendor performance management, and performance analytics as well as governance, risk, and compliance; and application development services.

ServiceNow Careers

Join the dynamic team at ServiceNow, a global leader in digital workflow solutions, where innovation and leadership converge to shape the future of work. At ServiceNow, we offer more than just job opportunities; we provide a platform for professional growth and a chance to be part of a culture that values diversity, creativity, and continuous learning.

Work You’ll Do

Embark on a career journey with ServiceNow and contribute to the world’s leading enterprises' digital transformation. Our team is at the forefront of developing cutting-edge technologies that improve how people work. With ServiceNow, you will use your skills to impact businesses and industries profoundly, driving efficiency and innovation.

Join Our Market-Leading Team

ServiceNow is not just another technology company. We are a team that thrives on diversity and leadership, fostering an inclusive environment that promotes growth and development. Our commitment to diversity training ensures that every team member can achieve their potential.

Innovative Work

ServiceNow is home to more than 10,000 dedicated professionals who lead the charge in digital workflows and enterprise solutions. As part of our team, you will engage in projects that merge technology with practical applications, creating revolutionary products that advance how services are delivered and managed.

Career Development

At ServiceNow, your career trajectory is filled with boundless opportunities. We support your growth with robust training programs, leadership development courses, and access to global challenges. Whether you are looking for an internship, full-time position, or leadership role, ServiceNow equips you with the tools to excel.

Be Part of a Great Team

Working at ServiceNow means being part of a community that values teamwork and innovation. Our collaborative environment encourages networking and sharing ideas, making our workplace vibrant and dynamic. The benefits of joining ServiceNow extend beyond comprehensive health and wellness; they include fostering professional connections and friendships that last a lifetime.

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Learn more about ServiceNow
Size
16,881 employees
Market Cap
$76.5 billion
Industry
Information Technology
Net Income
$118.5 million
Founded
2004
5 Year Trend
+33.5%
Revenue
$4.5 billion
NASDAQ
NOW
* Ladders Estimates

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