Staff Software Engineer

ServiceNow•Santa Clara, CA

13h•$166,500 - $291,400•Hybrid

About The Position

ServiceNow is looking for a Staff Software Engineer to help design, build, and operate the next generation of AI-powered platform services. This role requires a strong software engineer and technical lead with deep software design and architecture skills, strong coding ability, and the technical judgment to build reliable production systems at enterprise scale. The team is modernizing the stack by building “off-Glide” Kubernetes-based microservices primarily written in Python, with integration points into Java and the broader ServiceNow platform. The ideal candidate has built and operated containerized backend services in Kubernetes environments, understands distributed systems and production reliability, and can lead technical design across ambiguous problem spaces. Prior experience working on AI, GenAI, ML-powered, or data-intensive products is a strong plus.

Requirements

8+ years of professional software engineering experience, with strong fundamentals in data structures, algorithms, distributed systems, APIs, and backend service design.
Demonstrated experience as a technical lead, Staff Engineer, or equivalent senior individual contributor responsible for architecture, technical direction, code quality, and mentoring.
Strong backend engineering skills with hands-on experience designing, building, and operating production services.
Strong Python engineering skills, or demonstrated ability to quickly become productive in Python for backend service development.
Hands-on experience building or operating containerized applications deployed in Kubernetes, OpenShift, or similar orchestration environments.
Experience modernizing monolithic systems into microservices, distributed services, or independently deployable backend components.
Experience designing scalable APIs, asynchronous processing systems, queues, event-driven services, or data-processing pipelines.
Familiarity with cloud-native infrastructure, service observability, logging, monitoring, reliability engineering, and production troubleshooting.
Ability to make pragmatic architecture decisions across performance, reliability, security, maintainability, and delivery speed.
Strong coding skills and the ability to raise the engineering bar through code reviews, design reviews, and technical mentorship.
Strong communication skills and the ability to partner across product, engineering, infrastructure, security, and research-oriented teams.

Nice To Haves

10+ years of backend or distributed systems engineering experience.
Prior experience working on AI, GenAI, ML-powered, NLP, document processing, search, knowledge extraction, or data-intensive products.
Experience building large-scale document ingestion, document conversion, data transformation, or AI data pipeline systems.
Experience with production AI quality workflows, including model evaluation, benchmarking, golden datasets, regression testing, or automated release evaluation.
Working experience with frontier AI SDKs such as Anthropic, Google, or OpenAI.
Familiarity with prompt engineering, structured outputs, tool calling, agentic design patterns, Model Context Protocol, or AI-assisted development workflows.
Knowledge of MLOps or applying machine learning models to production use cases.
Experience with FastAPI or similar Python service frameworks.
Experience with infrastructure backends such as PostgreSQL, Redis, Kafka, RabbitMQ, S3-compatible object storage, or equivalent technologies.
Experience with CI/CD, automated deployment workflows, release management, DevOps, or operating services outside a centralized platform release process.
Experience with observability tools such as Prometheus, Grafana, Instana, or equivalent monitoring/logging platforms.
Experience with security ownership, vulnerability management, CVE triage, secure development practices, or enterprise compliance expectations.
Experience contributing to open-source or inner-source platforms, reusable frameworks, or shared infrastructure components.
Published work, patents, conference papers, or open-source contributions related to AI systems, knowledge systems, search, retrieval, or large-scale data processing.
Experience collaborating with research teams or translating advanced AI/ML capabilities into production software.
Experience mentoring engineers and helping them grow through design feedback, code review, onboarding, and technical coaching.

Responsibilities

Design, build, and operate production-grade AI platform microservices that run outside the traditional Glide Java codebase while still integrating cleanly with the broader ServiceNow ecosystem.
Build off-Glide Python microservices deployed on Kubernetes.
Design APIs, service boundaries, data models, and integration patterns for AI-enabled products.
Modernize monolithic workflows into scalable, independently deployable services.
Build reliable distributed systems that handle concurrency, queueing, retries, fairness, backpressure, and failure recovery.
Integrate frontier AI SDKs such as Anthropic, Google, and OpenAI into production software systems.
Apply prompt engineering, structured outputs, model evaluation, and production observability to GenAI use cases.
Design evaluation and benchmarking workflows for AI-powered product capabilities.
Partner with platform, product, security, and infrastructure teams to ship enterprise-grade services.
Raise the engineering bar through architecture reviews, code reviews, mentoring, and technical direction.