Principal Software Engineer – Compute Engineering
About The Position
The Principal Software Engineer joins ServiceNow’s Compute Engineering organization, which builds the scheduling, capacity, and performance systems that run its platform across private and public clouds. The role sets technical direction across multiple teams or a major compute area, shapes architecture, mentors senior engineers and architects, and influences decisions across geographies. The engineer designs and evolves compute scheduling and resource-management systems; develops capacity models and performance testing practices; and applies AI and machine learning to forecasting, anomaly detection, and placement optimization when those methods outperform simpler approaches. The role also maintains declarative, software-defined infrastructure and evaluates tools and methods that improve efficiency and reliability. This position partners with networking, orchestration, SRE, and FinOps teams; guides complex technical decisions and design reviews; owns production reliability and incident response for compute systems; and leads post-incident improvements. It also mentors architects and senior engineers and develops future technical leaders.
Requirements
- Experience leveraging or critically evaluating how to integrate AI into work processes, decision-making, or problem-solving.
- 15+ years of related software engineering, cloud, or infrastructure automation experience with a bachelor's degree; or 12+ years with a master's degree; or a Ph.D. with 8+ 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, and experience with related languages.
- Experience with capacity planning, performance engineering, or load testing at scale.
- Hands-on experience applying machine learning in production, including models, feature pipelines, or ML platforms; use of AI tools alone is not sufficient.
- Experience with infrastructure as code and configuration management, such as Terraform and Ansible.
- Comfort with virtualization and cloud infrastructure across private and public clouds, such as Azure, AWS, or GCP.
- Working understanding of IP networking, block and file storage, and load balancers.
- Ability to work independently across interconnected systems and investigate root causes without waiting for direction.
- Ability to influence without direct authority across multiple teams and geographies, including the US, EU, and India.
- Clear communication with senior leaders, customers, and engineers, including the ability to articulate a compelling technical vision.
- A learning mindset and motivation to build new skills and improve outcomes for internal and external customers.
- Integrity, honesty, and commitment to ServiceNow's values.
Nice To Haves
- 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.
Responsibilities
- Design and evolve compute schedulers and resource-management systems, including placement, prioritization, preemption, and workload fairness.
- Build capacity models and forecasts across private and public clouds and translate them into reservation and placement decisions.
- Establish performance and scale testing, including benchmarks, load tests, regression detection, and SLOs for scheduling latency and throughput.
- Apply AI and machine learning to forecasting, anomaly detection, and placement optimization when they outperform simpler approaches.
- Write and maintain declarative, software-defined infrastructure at scale, including 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 delivery 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.
- Set technical direction across multiple teams or a major compute area and influence decisions across geographies.
Benefits
- Health plans, including flexible spending accounts.
- 401(k) plan with company match.
- Employee stock purchase plan (ESPP).
- Matching donations.
- Flexible time away plan.
- Family leave programs.
- Equity, when applicable.
- Variable or incentive compensation.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
