Principal Software Engineer

ServiceNow-posted 2 months ago

$195,700 - $342,500/Yr

Full-time • Senior

San Diego, CA

5,001-10,000 employees

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The Intelligent Workflow Engineering organization is at the core of ServiceNow’s Automation and AI-native Platform vision. We design and deliver the next generation of flow orchestration, automation, and decisioning capabilities that power how enterprises digitize and optimize their work. Our portfolio includes foundational products such as Flow Designer and the Flow Engine, Process Automation Designer, Playbooks, Decision Management, RPA and WebAgent Automations, Process and Task Mining, Notifications, Adoption Services, and Document Management. Together, these form the Automation suite — the backbone of how customers build, run, and scale automations on the Now Platform. We combine deep expertise in workflow execution, AI-driven orchestration, and distributed system design to enable the vision of 'Anybody can Automate Anything from Anywhere using the Power of AI'. Our systems are the execution fabric behind billions of transactions daily, integrating AI, analytics, and intelligent decisioning to deliver hyper-scalable, reliable, and data-aware automation experiences for our customers.

Lead the architecture, design, and evolution of our core backend and workflow engine frameworks, ensuring they are highly scalable, performant, and resilient across millions of transactions and automation flows.
Drive major initiatives related to the integration of AI, automation, and flow orchestration into our platform’s core engine, enabling next-generation intelligent workflows.
Evaluate, design, and champion distributed systems architectures, messaging frameworks, and data persistence strategies that ensure low-latency, high-throughput performance at enterprise scale.
Mentor and guide engineers across multiple teams, fostering a culture of technical depth, performance-first thinking, and engineering excellence.
Collaborate with product managers, architects, and UI engineers to translate complex workflow and automation requirements into elegant, extensible, and fault-tolerant backend systems.
Champion observability, reliability, and efficiency through strong design principles, metrics-driven performance tuning, and advanced debugging practices.
Build high-quality, clean, modular, and reusable code by enforcing best practices around system design, API contracts, testing, and code reviews.
Work with product owners and AI/automation leads to own features end-to-end — from architectural design and performance modeling to deployment and continuous optimization.
Design and implement backend services that empower customers to build, execute, and monitor complex workflows at scale, while ensuring extensibility and configurability.
Contribute to the design and implementation of new workflow engine features and performance frameworks, while continuously enhancing the scalability and reliability of the existing ecosystem.
Plan, lead, and execute large-scale backend modernization and re-platforming efforts, considering architectural trade-offs, system risks, and long-term maintainability.
You will architect and build core services, orchestration engines, and asynchronous processing frameworks that power the automation and AI fabric of the platform — running both on our infrastructure and across public clouds.
Develop robust backend integrations with other systems and services using REST, gRPC, and event-driven paradigms, ensuring secure, performant, and maintainable interfaces.
Collaborate closely with infrastructure and platform engineering teams to optimize deployment pipelines, runtime performance, and scalability across multi-tenant environments.

Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
Proven experience in building workflow engines, orchestration frameworks, message queues, or event-driven architectures.
Strong background in distributed systems, microservices architecture, and data consistency patterns (CQRS, Saga, eventual consistency, etc.).
Exposure to or collaborating with AI research teams, applied ML systems, or large-scale data platforms is highly desirable.
Deep understanding of scale, performance, and reliability engineering — including load testing, capacity planning, and latency analysis.
Demonstrated track record of innovation — conceptualizing, prototyping, and implementing new ideas that improve platform capabilities or developer productivity.
15 years of related experience with a Bachelor's degree; or 12 years and a Master's degree; or a PhD with 8 years experience; or equivalent experience.
Proficiency in API design (REST, GraphQL, gRPC) and secure service communication patterns.
Strong foundation in asynchronous programming, multi-threading, and non-blocking I/O.
Experience with observability tooling (Grafana, Prometheus, OpenTelemetry, ELK) and distributed tracing.
Strong understanding of CI/CD, automated testing, and blue-green or canary deployment models.
Proven ability to lead architectural discussions, drive complex technical decisions, and mentor senior engineers.
Experience with AI-native or automation platforms is a strong plus (e.g., ServiceNow Flow Designer, RPA, Task Mining, Process Mining).
Excellent communication skills with a collaborative mindset across cross-functional teams.

Exposure to or collaborating with AI research teams, applied ML systems, or large-scale data platforms.

Base pay of $195,700 - $342,500, plus equity (when applicable), variable/incentive compensation and 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.

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