Jobs / United States / ServiceNow UK Limited

ServiceNow UK Limited

Senior Staff Software Engineer - AI/ML Inference Engineering

Kirkland, Washington, US; San Diego, CALIFORNIA, US; Santa Clara, CALIFORNIA, US Posted today $201,300 - $352,300

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Skills this job asks for

Machine learningServiceNowKubernetesLLMsPythonCI/CD

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Sponsorship verdict

No sponsorship evidence yet

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  • Confirmed live todayWhen a source last listed this job as open.
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No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

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About the role

What you get to do in this role: About the team -  The AI Services Platform Group at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future. We are seeking a Senior Staff Software Engineer - AI/ML Inference Engineering to lead the architecture, optimization, and operational excellence of our AI inference platform. You will own the end-to-end inference lifecycle—from onboarding cutting-edge models to deploying optimized inference engines in production across multiple backends on Kubernetes infrastructure. You'll also architect the intelligent gateway layer using Envoy and ext_proc to enforce access control, provide observability, and enable advanced request routing. This role combines deep technical expertise in GPU compute, LLM APIs, inference frameworks, containerization, orchestration, and API gateway architecture with a bias toward pragmatic engineering and measurable performance impact.  To be successful in this role you have: • Expertise in Go or Python, OOP, Design Patterns, time and space-efficient algorithms • Model-serving and runtime experience, such as vLLM, TensorRT-LLM, Triton Inference Server. • Exposure to LLM APIs or ML-serving systems, or a clear ability to ramp up quickly • Experience building new products that use challenging algorithms • Expertise in coding efficient, object-oriented, modularized and quality software • Knowledge of core AI/ML techniques and algorithms • Knowledge of unit testing, profiling, and code tuning AI skills  Artificial intelligence strategy is a critical skill at Experienced proficiency for IC5 — it applies to how you build and to what you build.  • Confident use of AI coding assistants such as GitHub Copilot or Cursor, paired with the critical eye to review AI-generated code as rigorously as any other — catching logic errors, security anti-patterns, and missed edge cases rather than treating model output as production-ready.  • AI-assisted debugging and trace analysis, and a clear understanding of the data privacy rules governing what goes into a prompt. Mandatory minimum  • 8+ years of Backend software engineering experience  • 4+ years of designing and operating distributed systems  • Bachelor’s degree in computer science, software engineering, or a closely related technical field required. • A master’s degree may offset up to one year of the experience minimum. Equivalent practical experience is considered where technical depth is clearly demonstrable. Desired skills: • Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines that make releases repeatable and safe to roll back.  • Own observability for what you build — meaningful metrics, useful logs, real tracing, and alerts that fire on customer impact rather than on noise.  • Debug and resolve production incidents independently, participate in on-call, run root-cause analysis, and operate against defined service level objectives.    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

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