Senior Staff Software Engineer – Compute Engineering

Job description

We are hiring across multiple engineering levels. Final level alignment is determined by experience, technical expertise, demonstrated impact, and interview performance. Join the Compute Engineering organization, which builds the scheduling, capacity, and performance systems that run our platform across private and public cloud.

What you get to do in this role

Design and evolve the compute scheduler and resource-management systems, including placement, prioritization, preemption, and fairness across workloads. Build capacity models and forecasts across private and public cloud, and turn them into reservation and placement decisions.

Establish performance and scale testing

benchmarks, load tests, regression detection, and SLOs for scheduling latency and throughput. Apply AI and ML to forecasting, anomaly detection, and placement optimization where they outperform simpler approaches. Write and maintain declarative, software-defined infrastructure at scale, with build systems, web services, and automation that are specified, documented, and testable. Research and adopt open-source and commercial tools and methods that improve compute efficiency and reliability.

Partner with networking, orchestration, SRE, and FinOps teams on cross-team designs and cost trade-offs. Guide complex technical decisions and design reviews. Challenge assumptions with data, surface architectural risks early, and balance shipping speed with long-term durability. Own production reliability and incident response for compute systems, and lead post-incident improvements. Mentor architects and senior engineers and build the next layer of technical leadership.

Level expectations Senior Staff

Leads the design and delivery of a major component of the compute platform. Drives quality within a team and mentors engineers.

Principal

Sets technical direction across multiple teams or a major compute area. Shapes architecture, mentors senior engineers and architects, and influences decisions across geographies.

Qualifications

Qualifications

To be successful in this role you have: 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. 12+ years of related experience in software engineering, cloud, or infrastructure automation with a Bachelor's degree; or 8+ years and a Master's degree; or a PhD with 5+ years of experience; or equivalent experience.

Deep experience designing multi-tenant, cloud-native SaaS at enterprise scale, including distributed systems, large-scale data systems, APIs, and microservices. Experience designing or operating large-scale schedulers or resource managers, such as Kubernetes, Slurm, or internal equivalents. Strong programming skills in Go, Python, or Java, with experience in related languages. Experience with capacity planning, performance engineering, or load testing at scale.

Hands-on experience applying ML in production, including models, feature pipelines, or ML platforms. Using AI tools alone is not enough. Experience with infrastructure as code and configuration management, such as Terraform and Ansible. Comfortable with virtualization and cloud infrastructure across private and public clouds, such as Azure, AWS, GCP. Working understanding of IP networking, block and file storage, and load balancers.

Experience integrating AI into work processes, decision-making, or problem solving. Works independently across interconnected systems and investigates root causes without waiting for direction. Influences without direct authority across multiple teams and geographies (US, EU, India). Communicates clearly with senior leaders, customers, and engineers, and articulates a compelling technical vision. Has a learning mindset and is motivated to build new skills and bring real improvement to internal and external customers.

Has integrity and honesty, and upholds ServiceNow's values. Preferred Experience with ML-driven scheduling, forecasting, or capacity optimization. Working knowledge of internet protocols such as DNS, NTP, and HTTP. Experience with release management and large-scale server infrastructure. For positions in this location, we offer a base pay of $190,900 - $334,100 , 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.