Staff Software AIML Engineer

Staff Software Engineer AI Native Development

AI Security Incubation & Innovation

Security and Risk Engineering

About the team

The Security and Risk Engineering organization builds scalable AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking clean architecture intuitive experiences and a culture of continuous learning.

This is a zero-to-one incubation. Were building a new class of exposure analysis that ranks security work by exploitabilitywhere an attacker could realistically get inrather than raw severity. The architecture is evolving and this role helps define what good looks like.

The Role

As a Staff Software Engineer AI Native Development you will be a hands-on technical leader responsible for the architecture design delivery and evolution of major AI-powered software systems and subsystems.

You will combine deep full-stack software engineering expertise with strong AI/ML-native development skills to solve complex ambiguous problems and build production-grade systems at scale. You will own significant technical areas end-to-endfrom user experiences and APIs to distributed services data and retrieval systems AI/ML capabilities and cloud infrastructure.

Beyond your individual contributions you will provide technical direction across a broader engineering area make critical architecture and design decisions establish engineering standards and influence multiple engineers and teams. You will help shape how we build AI-native products and establish the technical foundation for the next generation of intelligent enterprise applications.

This is a role for an engineer who can operate effectively at both architectural altitude and implementation depthsomeone who can define the direction make the difficult technical decisions and still dive into the code when needed.

What Youll Own

• A major product or technical subsystem end-to-end including its architecture design implementation scalability reliability security and ongoing evolution.
• The technical vision and architecture for your area including key design decisions and interfaces with other systems and teams.
• The quality and business/technical outcomes of your subsystem with measurable targets for reliability performance AI quality latency cost and customer impact.
• The architecture and engineering practices required to build AI-native applications at production scale.
• Technical direction for engineers working within your area providing guidance through architecture design reviews code reviews and hands-on technical leadership.
• The evolution of AI/ML capabilities such as agentic workflows retrieval model integration evaluation and intelligent automation within your product area.
• The technical strategy for balancing AI capability engineering complexity reliability security latency and cost.

What Youll Do

Technical & Architectural Leadership

• Take highly ambiguous and complex problems and turn them into clear technical strategies architectures and executable plans.
• Own the architecture of major systems or subsystems and drive them from concept through production at scale.
• Make sound technical decisions under uncertainty and clearly articulate architectural trade-offs.
• Define system boundaries interfaces APIs data flows and integration patterns across multiple services and teams.
• Drive architecture and design reviews and establish a high engineering bar for scalability reliability security maintainability and performance.
• Identify architectural risks and technical debt and drive long-term improvements across your area.
• Influence technical direction beyond your immediate team through strong technical judgment and collaboration.

Full-Stack Engineering

• Remain hands-on in building complex software across the stack from frontend experiences and APIs to backend services data systems AI services and cloud infrastructure.
• Design scalable full-stack architectures using technologies such as React TypeScript Python Java Go and modern cloud-native platforms.
• Build distributed services event-driven systems APIs databases caching messaging and scalable data pipelines.
• Ensure systems are observable resilient secure and operationally excellent in production.
• Lead by example through high-quality implementation testing debugging code reviews and engineering practices.

AI/ML-Native Development

• Define and drive the adoption of AI-native architectures and engineering patterns across your technical area.
• Design and build production-grade LLM and agentic systems including:
  • Multi-agent orchestration
  • Tool and function calling
  • Planning and reasoning loops
  • Context and memory management
  • Retrieval and grounding
  • Failure recovery and resilience
  • Human-in-the-loop workflows
• Integrate frontier models from providers such as OpenAI Anthropic Google or equivalent platforms making informed decisions around model capability cost latency and reliability.
• Design RAG and retrieval systems using embeddings vector search hybrid search semantic retrieval re-ranking and enterprise data sources.
• Establish robust AI evaluation strategies and measurable quality metrics for AI-powered functionality.
• Drive AI observability covering model quality latency cost failures hallucination/error rates and system behavior.
• Establish appropriate AI safety security governance privacy and guardrail mechanisms for production systems.
• Evaluate emerging AI capabilities and determine how and where they can create meaningful product or engineering value.

Technical Leadership & Influence

• Provide technical direction and mentorship to engineers across the workstream.
• Lead complex engineering initiatives through influence rather than organizational authority.
• Mentor senior and emerging engineers on architecture system design full-stack development and production AI practices.
• Partner closely with product design platform data security and other engineering organizations to translate customer problems into scalable technical solutions.
• Facilitate technical alignment across teams and resolve architectural disagreements through data experimentation and sound engineering judgment.
• Establish reusable patterns frameworks libraries and engineering practices that improve productivity across teams.
• Help define the organizations approach to AI-native software development and AI-assisted engineering.

AI-Assisted Development

• Champion effective use of AI coding agents and development tools such as Claude Code Codex Cursor Windsurf or equivalent technologies.
• Establish engineering practices for using AI to accelerate development while maintaining code quality security testing and accountability.
• Identify opportunities to use AI across the software development lifecycle including design implementation testing debugging documentation and code review.
• Share learnings and establish best practices that enable teams to become more effective AI-native engineering organizations.

What You Bring

• A strong track record of owning significant software systems or subsystems end-to-end in production.
• Deep full-stack engineering expertise with the ability to work across frontend backend APIs data AI services and cloud infrastructure.
• Strong understanding of distributed systems system architecture data structures algorithms APIs databases scalability reliability and cloud-native development.
• Expert-level programming experience in Python Java Go TypeScript or equivalent languages.
• Hands-on experience designing and delivering AI/ML-powered production systems.
• Strong practical knowledge of modern AI technologies including LLMs RAG embeddings vector search agentic workflows tool calling model evaluation and AI observability.
• Experience taking ambiguous problems from concept and experimentation through reliable production systemsthat other engineers or product

Qualifications :

• 8 years of software engineering experience or equivalent practical experience.
• Experience designing and delivering production software systems.
• Experience building or integrating AI/ML-powered applications in a production or near-production environment.
• Modern AI experience: LLMs RAG embeddings vector search agentic workflows model evaluation or AI observability.
• Strong programming experience in Python and/or Java Go or a similar language.
• Cloud-native technologies distributed systems APIs databases and scalable architectures.
• Bachelors or Masters degree in Computer Science Artificial Intelligence Machine Learning or a related technical discipline or equivalent practical experience.
• Cybersecurity or security-product experience is a plus.

FD21

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 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 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. 

From Fortune. 2026 Fortune Media IP Limited. All rights reserved. Used under license.

Remote Work :

No

Employment Type :

Full-time