Senior Staff Software Engineer – Compute Engineering

ServiceNow; Santa Clara (CA); Hybrid; USD 191,000 - 334,000; Full time

Benefits offered by this job

Health plans

401(k) plan

ESPP

Donations matching

Flexible time away

Job summary

ServiceNow in Santa Clara, CA, is hiring across multiple engineering levels for compute engineering focused on scheduling, capacity, and performance across private and public clouds. You will design and evolve schedulers, build models, and apply AI/ML to improve forecasting and placement, while ensuring reliability and scale.

The role requires deep experience in large-scale SaaS, multi-tenant architectures, and proficiency in Go, Python, or Java.

Qualifications

• 12+ years of related software engineering/cloud/infrastructure automation experience with a Bachelor's, or 8+ years with a Master's, or PhD with 5+ years.
• Deep experience designing multi-tenant cloud-native SaaS at enterprise scale, including distributed data systems and APIs.
• Experience designing or operating large-scale schedulers or resource managers (Kubernetes, Slurm, or equivalents).
• Strong programming skills in Go, Python, or Java.
• Experience with capacity planning, performance engineering, or load testing at scale.
• Hands-on experience applying ML in production (models, pipelines, platforms).
• Experience with infrastructure as code and configuration management (Terraform, Ansible).
• Comfortable with virtualization and cloud infra (Azure, AWS, GCP).
• Working understanding of IP networking, storage, and load balancers.

Responsibilities

• Design and evolve compute scheduler and resource-management systems, including placement and fairness.
• Build capacity models and forecasts for private/public cloud to inform placement decisions.
• Establish performance tests, benchmarks, regression detection, and SLOs for scheduling latency/throughput.
• Apply AI/ML to forecasting and placement optimization where advantageous.
• Write declarative infrastructure code and web services with testable automation.
• Research and adopt tools/methods to improve compute efficiency and reliability.
• Partner with networking, orchestration, SRE, and FinOps for cross-team designs and cost trade-offs.
• Guide complex technical decisions and balance speed with long-term durability.
• Own production reliability and incident response for compute systems; lead post-incident improvements.
• Mentor architects and senior engineers to build leadership.

Skills

Cloud-native SaaS design

Scheduler design

Go / Python / Java

Capacity planning

ML in production

IaC (Terraform/Ansible)

Cloud platforms (Azure AWS GCP)

Networking fundamentals

Release management

Communication

Education

Bachelor's degree or higher

Tools

Kubernetes

Slurm

Job description

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.

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.

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 [e-mail] 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.

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