Senior Staff Software Engineer - Agentic AI
ServiceNow · Santa Clara, CA · 1 mo ago
HybridEngineeringFull-time
We need to output HTML fragment with sections: About the role? Actually the posting includes Company Description, Job Description, Qualifications, Additional Information (Work Personas, etc). We must not repeat job title as heading. Use for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to map content accordingly.
We need to extract substantive info: Company Description (maybe as About the role? Actually "Company Description" could be considered "About the role"? But they said use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can have sections: About the role (company description + maybe overview), Responsibilities (the "What You Get To Do In This Role" bullet points), Requirements (Qualifications), Skills (maybe from qualifications list), Benefits (if any). The posting does not mention Pay, Schedule, Benefits explicitly. Additional Information includes Work Personas (flexible/remote) but that's not benefits; maybe we can include as a short paragraph under About the role? But we should not create sections with filler. Benefits not stated, so omit Benefits, Pay, Schedule.
We need to preserve all substantive info, not invent. So we need to include company description paragraph, responsibilities list (the many bullet points under "What You Get To Do In This Role" broken into categories). We need to turn them into
for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to map content accordingly.
We need to extract substantive info: Company Description (maybe as About the role? Actually "Company Description" could be considered "About the role"? But they said use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can have sections: About the role (company description + maybe overview), Responsibilities (the "What You Get To Do In This Role" bullet points), Requirements (Qualifications), Skills (maybe from qualifications list), Benefits (if any). The posting does not mention Pay, Schedule, Benefits explicitly. Additional Information includes Work Personas (flexible/remote) but that's not benefits; maybe we can include as a short paragraph under About the role? But we should not create sections with filler. Benefits not stated, so omit Benefits, Pay, Schedule.
We need to preserve all substantive info, not invent. So we need to include company description paragraph, responsibilities list (the many bullet points under "What You Get To Do In This Role" broken into categories). We need to turn them into - . Could group under responsibilities heading.
Qualifications: list of requirements (the numbered list). We'll put under Requirements heading (or Qualifications). They said use Requirements heading for list of duties/requirements/benefits. So we can have
Requirements
with .
Skills: maybe we can extract skill-specific items from qualifications (like Expert-level proficiency in Python, Java, JavaScript/GlideScript; deep expertise with ServiceNow scripting, APIs, platform architecture; etc.) Could put under Skills heading. But we must not create thin sections; better to combine qualifications and skills? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have both Requirements and Skills if content exists. We have qualifications list that includes both experience requirements and skill proficiencies. Could split: Requirements heading for experience/education, Skills heading for technical proficiencies. But we must ensure not to create filler.
Let's parse qualifications block:
"To Be Successful in this role you have:
12+ years of software development experience with a Bachelor's degree; OR 8+ years with a Master's degree; OR 5+ years with a PhD; OR equivalent work experience
4+ years in cloud-native and AI-native systems or equivalent senior-level roles
5+ years of experience with LLM/AI systems at scale, including prompt engineering, agent design, retrieval systems, and production AI/ML services
5+ years of hands-on experience building and scaling systems with third-party AI/ML services and platform APIs across multiple cloud providers
3+ years of experience designing and building applications on platform-as-a-service or SaaS platforms; deep expertise with ServiceNow platform at scale
Expert-level proficiency in Python, Java, and JavaScript/GlideScript; deep expertise in ServiceNow scripting, APIs, and platform architecture
Demonstrated expertise in distributed systems design, microservices architecture, and large-scale systems
Proven track record designing high-performance, mission-critical data pipelines, embedding systems, and vector databases
Expert knowledge of LLM orchestration frameworks, RAG architectures, retrieval optimization, and vector database technologies
Deep expertise with cloud computing (AWS/GCP/Azure), managed AI services, and infrastructure-as-code
Strong background in Kubernetes, containerization, and cloud-native deployment patterns
Expertise in building evaluation frameworks, metrics systems, and production monitoring for AI/ML systems
Experience with and strong opinions about secure coding practices, responsible AI, and compliance requirements
Exceptional communication skills; ability to influence across levels of technical seniority and non-technical audiences; demonstrated customer engagement experience
Proven ability to lead large, cross-functional technical initiatives; track record of significant technical accomplishments
Strong background in software architecture, system design, and technical strategy; experience shaping platform strategy and roadmap
Experience mentoring senior engineers, engineering managers, or technical leaders
Experience leading customer-critical initiatives or providing technical leadership on strategic accounts
Bachelor's degree in computer science, engineering, or related field; advanced degree or significant AI/ML research/publications is a plus
Active engagement with the broader engineering and AI/ML community (conferences, publications, open-source, etc.)
Demonstrated thought leadership in AI-native development, cloud architecture, or software engineering"
We can separate: Requirements (experience/education) and Skills (technical proficiencies). Let's define Requirements as the first few bullet items about years of experience, degrees, etc. Skills as the rest.
Now Responsibilities: The "What You Get To Do In This Role" includes many bullet-like paragraphs grouped under headings: Technical Vision & Strategy, Organizational Leadership & Mentorship, Architecture & Systems Design, Cross-Organizational Influence & Communication, Software Development Excellence & Innovation, ServiceNow Platform Strategy & Excellence, Customer Strategy & Support Leadership. We can combine all into a single responsibilities list, but better to keep as subheadings? The instruction only allows headings from the list; we could still use for each of those subheadings? They said use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but they gave examples. Safer to stick to those headings only. So we will have one Responsibilities section containing all responsibilities as a list.
We need to preserve all substantive info; we can break into multiple - items each representing a responsibility bullet. We'll need to parse the long paragraphs into discrete items.
Let's extract responsibilities from the text:
Under "Technical Vision & Strategy":
- Define technical vision and strategy for AI-native and cloud-native systems; establish multi-year technology roadmaps and architectural patterns
- Lead the development of core platforms and infrastructure that enable AI-native development at scale (evaluation frameworks, monitoring, security, deployment)
- Drive adoption of emerging AI/ML technologies, frameworks, and best practices; assess new services and tools for organizational fit
- Establish and evolve technical standards, architectural principles, and engineering excellence standards across the organization
- Own the technical roadmap for critical business initiatives involving AI; evaluate feasibility and set realistic timelines
- Champion investment in foundational improvements (refactoring, testing infrastructure, monitoring, security) that have organization-wide impact
- Influence platform-level decisions involving cost, latency, reliability, and model quality; balance business objectives with technical constraints
- Stay at the forefront of AI/ML research and industry trends; translate research into practical applications for the business
Under "Organizational Leadership & Mentorship":
- Mentor and develop senior engineers (IC3/IC4) and engineering leaders; support their growth into leadership and architectural roles
- Lead technical hiring; assess candidates at senior levels and contribute to building a world-class engineering team
- Establish and enforce engineering culture focused on technical excellence, learning, ownership, and collaboration
- Lead by example in code quality, testing discipline, security practices, and responsible AI principles
- Support manager and team leadership development; provide technical guidance to engineering managers and team leads
- Conduct architectural and design reviews; provide critical feedback that shapes the quality of technical decisions across the organization
- Foster knowledge sharing through documentation, technical talks, open-source contributions, and community engagement
- Create and refine career paths and professional development opportunities for engineering team members
Under "Architecture & Systems Design":
- Design and architect large, complex systems involving multiple teams, cloud infrastructure, and sophisticated AI/ML components
- Lead the design of evaluation frameworks, observability systems, and production monitoring for AI-driven features at scale
- Establish security architecture and responsible AI guardrails that scale across the platform
- Design high-performance data platforms, embedding systems, and retrieval pipelines that serve organization-wide needs
- Evaluate and guide adoption of new cloud services, managed AI services, and technologies
- Drive architectural decisions that balance competing concerns: performance, cost, scalability, reliability, developer experience, and business value
- Conduct research and prototyping on novel technical approaches; lead exploration of emerging AI/ML techniques
- Lead root cause analysis and architectural reviews for critical incidents; drive improvements to prevent recurrence
Under "Cross-Organizational Influence & Communication":
- Communicate technical vision and strategy to executives, product leadership, and engineering teams; influence organizational priorities
- Partner with product, design, and domain specialists to define ambitious technical roadmaps aligned with business strategy
- Represent the engineering organization in high-stakes customer and partnership discussions; build credibility and trust
- Lead or contribute to technical due diligence for acquisitions, partnerships, and strategic technology evaluations
- Translate complex AI/ML concepts, trade-offs, and limitations for audiences ranging from technical engineers to executive leadership
- Advocate for technical health, engineering culture, and long-term sustainability over short-term pressures
- Participate in industry forums, conferences, and communities; enhance the organization's external reputation
- Lead technical interviews and design discussions; mentor interviewing skills across the engineering organization
Under "Software Development Excellence & Innovation":
- Develop innovative solutions to the organization's most complex technical challenges, particularly around AI/ML integration and distributed systems
- Prototype and validate new approaches; share learnings and best practices across the organization
- Contribute to critical code paths and architectures; model best practices in code quality, testing, and maintainability
- Build evaluation frameworks, monitoring systems, and testing infrastructure that scale across the organization
- Implement security best practices, responsible AI guardrails, and compliance mechanisms that serve as templates for the organization
- Work with cloud services, managed AI services, Kubernetes, and infrastructure-as-code at an architectural level
- Troubleshoot and resolve the most complex production issues; establish practices to prevent future incidents
- Contribute to open-source projects, research initiatives, or industry collaboration where aligned with business strategy
Under "ServiceNow Platform Strategy & Excellence":
- Define platform architecture and integration patterns for AI-native ServiceNow applications
- Establish best practices and architectural standards for ServiceNow development across the organization
- Lead technical decisions on ServiceNow platform capabilities vs. custom development trade-offs
- Drive adoption of ServiceNow platform features and managed services; evaluate and recommend platform upgrades
- Partner with ServiceNow product teams and technical account managers on advanced integrations and customizations
- Mentor senior engineers on ServiceNow platform architecture and advanced development patterns
- Ensure applications remain compatible with ServiceNow platform updates and evolution
Under "Customer Strategy & Support Leadership":
- Shape organizational approach to customer support and issue resolution; establish standards for response and resolution
- Lead customer-critical incident response and complex troubleshooting; provide technical escalation path
- Engage with strategic customers on technical topics, roadmap alignment, and complex integration challenges
- Gather and synthesize customer feedback to inform product and platform strategy
- Establish programs and practices that improve customer experience and reduce support burden
- Work with customer success leadership to align technical capabilities with customer success metrics
- Lead technical due diligence and support in customer selection and onboarding processes
Now we need to output HTML fragment with sections: About the role (company description), Responsibilities (list), Requirements (list), Skills (list). Possibly also include Qualifications heading? But we already have Requirements and Skills. The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we could have both Requirements and Qualifications? Might be redundant. Better to follow the list: we can use Requirements for experience/education, Skills for technical proficiencies. We'll omit Qualifications heading to avoid duplication.
Now About the role: Should include company description paragraph(s). The 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
Requirements
with- .
Skills: maybe we can extract skill-specific items from qualifications (like Expert-level proficiency in Python, Java, JavaScript/GlideScript; deep expertise with ServiceNow scripting, APIs, platform architecture; etc.) Could put under Skills heading. But we must not create thin sections; better to combine qualifications and skills? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have both Requirements and Skills if content exists. We have qualifications list that includes both experience requirements and skill proficiencies. Could split: Requirements heading for experience/education, Skills heading for technical proficiencies. But we must ensure not to create filler.
Let's parse qualifications block:
"To Be Successful in this role you have:
12+ years of software development experience with a Bachelor's degree; OR 8+ years with a Master's degree; OR 5+ years with a PhD; OR equivalent work experience
4+ years in cloud-native and AI-native systems or equivalent senior-level roles
5+ years of experience with LLM/AI systems at scale, including prompt engineering, agent design, retrieval systems, and production AI/ML services
5+ years of hands-on experience building and scaling systems with third-party AI/ML services and platform APIs across multiple cloud providers
3+ years of experience designing and building applications on platform-as-a-service or SaaS platforms; deep expertise with ServiceNow platform at scale
Expert-level proficiency in Python, Java, and JavaScript/GlideScript; deep expertise in ServiceNow scripting, APIs, and platform architecture
Demonstrated expertise in distributed systems design, microservices architecture, and large-scale systems
Proven track record designing high-performance, mission-critical data pipelines, embedding systems, and vector databases
Expert knowledge of LLM orchestration frameworks, RAG architectures, retrieval optimization, and vector database technologies
Deep expertise with cloud computing (AWS/GCP/Azure), managed AI services, and infrastructure-as-code
Strong background in Kubernetes, containerization, and cloud-native deployment patterns
Expertise in building evaluation frameworks, metrics systems, and production monitoring for AI/ML systems
Experience with and strong opinions about secure coding practices, responsible AI, and compliance requirements
Exceptional communication skills; ability to influence across levels of technical seniority and non-technical audiences; demonstrated customer engagement experience
Proven ability to lead large, cross-functional technical initiatives; track record of significant technical accomplishments
Strong background in software architecture, system design, and technical strategy; experience shaping platform strategy and roadmap
Experience mentoring senior engineers, engineering managers, or technical leaders
Experience leading customer-critical initiatives or providing technical leadership on strategic accounts
Bachelor's degree in computer science, engineering, or related field; advanced degree or significant AI/ML research/publications is a plus
Active engagement with the broader engineering and AI/ML community (conferences, publications, open-source, etc.)
Demonstrated thought leadership in AI-native development, cloud architecture, or software engineering"
We can separate: Requirements (experience/education) and Skills (technical proficiencies). Let's define Requirements as the first few bullet items about years of experience, degrees, etc. Skills as the rest.
Now Responsibilities: The "What You Get To Do In This Role" includes many bullet-like paragraphs grouped under headings: Technical Vision & Strategy, Organizational Leadership & Mentorship, Architecture & Systems Design, Cross-Organizational Influence & Communication, Software Development Excellence & Innovation, ServiceNow Platform Strategy & Excellence, Customer Strategy & Support Leadership. We can combine all into a single responsibilities list, but better to keep as subheadings? The instruction only allows headings from the list; we could still use
- items each representing a responsibility bullet. We'll need to parse the long paragraphs into discrete items. Let's extract responsibilities from the text: Under "Technical Vision & Strategy": - Define technical vision and strategy for AI-native and cloud-native systems; establish multi-year technology roadmaps and architectural patterns - Lead the development of core platforms and infrastructure that enable AI-native development at scale (evaluation frameworks, monitoring, security, deployment) - Drive adoption of emerging AI/ML technologies, frameworks, and best practices; assess new services and tools for organizational fit - Establish and evolve technical standards, architectural principles, and engineering excellence standards across the organization - Own the technical roadmap for critical business initiatives involving AI; evaluate feasibility and set realistic timelines - Champion investment in foundational improvements (refactoring, testing infrastructure, monitoring, security) that have organization-wide impact - Influence platform-level decisions involving cost, latency, reliability, and model quality; balance business objectives with technical constraints - Stay at the forefront of AI/ML research and industry trends; translate research into practical applications for the business Under "Organizational Leadership & Mentorship": - Mentor and develop senior engineers (IC3/IC4) and engineering leaders; support their growth into leadership and architectural roles - Lead technical hiring; assess candidates at senior levels and contribute to building a world-class engineering team - Establish and enforce engineering culture focused on technical excellence, learning, ownership, and collaboration - Lead by example in code quality, testing discipline, security practices, and responsible AI principles - Support manager and team leadership development; provide technical guidance to engineering managers and team leads - Conduct architectural and design reviews; provide critical feedback that shapes the quality of technical decisions across the organization - Foster knowledge sharing through documentation, technical talks, open-source contributions, and community engagement - Create and refine career paths and professional development opportunities for engineering team members Under "Architecture & Systems Design": - Design and architect large, complex systems involving multiple teams, cloud infrastructure, and sophisticated AI/ML components - Lead the design of evaluation frameworks, observability systems, and production monitoring for AI-driven features at scale - Establish security architecture and responsible AI guardrails that scale across the platform - Design high-performance data platforms, embedding systems, and retrieval pipelines that serve organization-wide needs - Evaluate and guide adoption of new cloud services, managed AI services, and technologies - Drive architectural decisions that balance competing concerns: performance, cost, scalability, reliability, developer experience, and business value - Conduct research and prototyping on novel technical approaches; lead exploration of emerging AI/ML techniques - Lead root cause analysis and architectural reviews for critical incidents; drive improvements to prevent recurrence Under "Cross-Organizational Influence & Communication": - Communicate technical vision and strategy to executives, product leadership, and engineering teams; influence organizational priorities - Partner with product, design, and domain specialists to define ambitious technical roadmaps aligned with business strategy - Represent the engineering organization in high-stakes customer and partnership discussions; build credibility and trust - Lead or contribute to technical due diligence for acquisitions, partnerships, and strategic technology evaluations - Translate complex AI/ML concepts, trade-offs, and limitations for audiences ranging from technical engineers to executive leadership - Advocate for technical health, engineering culture, and long-term sustainability over short-term pressures - Participate in industry forums, conferences, and communities; enhance the organization's external reputation - Lead technical interviews and design discussions; mentor interviewing skills across the engineering organization Under "Software Development Excellence & Innovation": - Develop innovative solutions to the organization's most complex technical challenges, particularly around AI/ML integration and distributed systems - Prototype and validate new approaches; share learnings and best practices across the organization - Contribute to critical code paths and architectures; model best practices in code quality, testing, and maintainability - Build evaluation frameworks, monitoring systems, and testing infrastructure that scale across the organization - Implement security best practices, responsible AI guardrails, and compliance mechanisms that serve as templates for the organization - Work with cloud services, managed AI services, Kubernetes, and infrastructure-as-code at an architectural level - Troubleshoot and resolve the most complex production issues; establish practices to prevent future incidents - Contribute to open-source projects, research initiatives, or industry collaboration where aligned with business strategy Under "ServiceNow Platform Strategy & Excellence": - Define platform architecture and integration patterns for AI-native ServiceNow applications - Establish best practices and architectural standards for ServiceNow development across the organization - Lead technical decisions on ServiceNow platform capabilities vs. custom development trade-offs - Drive adoption of ServiceNow platform features and managed services; evaluate and recommend platform upgrades - Partner with ServiceNow product teams and technical account managers on advanced integrations and customizations - Mentor senior engineers on ServiceNow platform architecture and advanced development patterns - Ensure applications remain compatible with ServiceNow platform updates and evolution Under "Customer Strategy & Support Leadership": - Shape organizational approach to customer support and issue resolution; establish standards for response and resolution - Lead customer-critical incident response and complex troubleshooting; provide technical escalation path - Engage with strategic customers on technical topics, roadmap alignment, and complex integration challenges - Gather and synthesize customer feedback to inform product and platform strategy - Establish programs and practices that improve customer experience and reduce support burden - Work with customer success leadership to align technical capabilities with customer success metrics - Lead technical due diligence and support in customer selection and onboarding processes Now we need to output HTML fragment with sections: About the role (company description), Responsibilities (list), Requirements (list), Skills (list). Possibly also include Qualifications heading? But we already have Requirements and Skills. The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we could have both Requirements and Qualifications? Might be redundant. Better to follow the list: we can use Requirements for experience/education, Skills for technical proficiencies. We'll omit Qualifications heading to avoid duplication. Now About the role: Should include company description paragraph(s). The 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