Senior Staff Applications Development Engineer (Applications Development)

ServiceNow; Santa Clara (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Generous family leave

Matched donations

Annual learning stipends

Flexible PTO

Competitive retirement plan

Paid volunteer time

Job summary

ServiceNow seeks a Senior Staff Software Engineer to design, build, ship, and operate AI-native enterprise applications across industry workflows, data models, and compliance requirements. You will work closely with customers as a forward deployed engineer, delivering solutions that integrate with their data, integrations, and channels.

You will mentor engineers, drive architecture, and own the end-to-end lifecycle from requirements to production.

Qualifications

• Extensive experience designing AI-native applications and agentic workflows.
• Strong ability to write precise, testable requirements for AI agents.
• Proven track record delivering production SaaS at scale.

Responsibilities

• Design, build, and operate AI-native enterprise applications.
• Lead forward deployed engagements with customers across teams.
• Mentor engineers and drive architectural direction.

Skills

AI/ML software engineering

Prompts and agentic instructions

JavaScript/TypeScript

System design

Forward deployed engineering

Education

Bachelor's degree in Computer Science or related field

Tools

React

Angular

Vue

REST APIs

SQL/NoSQL databases

Job description

• As a Senior Staff Software Engineer, you will design, build, ship, and operate AI-native industry applications whose most important logic often lives in natural language (instructions, prompts, tool descriptions, and guardrails) as much as in code
• You will work across the full software development lifecycle, and often embedded directly with customers as a forward deployed engineer, building against their data, integrations, and channels
• Alongside hands-on delivery, you will drive engineering excellence, mentor other engineers, and influence architecture and long-term platform direction across multiple teams
• Design, build, and deliver scalable, AI-native enterprise applications for industry-specific workflows, data models, and compliance requirements, along with the integrations and channels that make them usable in production
• Build agentic behavior into those applications: intent interpretation, multi-step reasoning, tool and function invocation, and action on the user’s behalf, delivered through conversational experiences across chat (and voice where the use case calls for it) that hold context and hand off cleanly between automated and human agents
• Design AI-driven autonomous workflows: decompose business processes into the steps and decision points an agent can execute, decide where autonomy is appropriate and where a human checkpoint is required, and define how exceptions, retries, and hand-back to a person are handled
• Author and maintain agentic instructions (system instructions, role definitions, tool descriptions, guardrails, and escalation rules) as versioned engineering artifacts under review and regression coverage, not configuration text
• Engineer prompts for reliability rather than demo quality, iterating against measured outcomes: task decomposition, golden examples, structured output schemas, grounding and citation, graceful failure, and token and latency cost
• Build automated evaluation and test non-deterministic behavior: golden datasets, multi-turn conversation suites, model-as-judge scoring calibrated to human review, CI gates, drift detection, and adversarial, jailbreak, grounding, and tool-selection testing
• Design software that lets customers configure and extend platform capabilities without sacrificing performance, reliability, or maintainability, and write clean, reusable, well-tested code following engineering best practices, including code reviews, unit testing, and test automation
• Specify precisely and direct AI coding agents: convert requirements into testable specifications with explicit scope, constraints, and acceptance criteria, decompose work into agent-sized tasks, and review agent output for correctness and maintainability. You own the result regardless of what produced it
• Deliver as a forward deployed engineer, embedded with customers when the work calls for it: building against their data, integrations, and channels, tuning instructions and evaluation sets in their environment, and returning with evidence that improves the product
• Own quality, safety, and reliability in production: monitor conversation quality, containment, hallucination, and unsafe actions, defend against prompt injection and data leakage, and feed production failures back into specifications and evaluation sets. Troubleshoot and optimize performance, scalability, and reliability across distributed systems
• Serve as a technical leader: mentor engineers, promote knowledge sharing, drive engineering best practices, and lead complex technical initiatives spanning multiple teams while influencing architecture and long-term platform direction
• Partner with product managers, designers, and stakeholders to translate complex business and regulatory requirements into scalable technical solutions, align on tradeoffs, and communicate capability, limitation, and risk clearly to non-engineers

Benefits

• Generous family leave
• Matched donations
• Annual learning stipends
• Flexible PTO
• Competitive retirement plan
• Paid volunteer time

A demonstrated track record of building, shipping, and operating production software, including hands-on delivery of AI-native application features that real users depend on rather than demosServiceNow platform experience is recommended, including building configurable, extensible applications on the platformAI-native application development: agent orchestration at the application layer, tool and function calling, context assembly, grounding against enterprise data, and handling latency, cost, and failureExperience with any of the modern UI frameworks like Angular, React or VueDemonstrated ability to lead technically complex projects across multiple teams as a technical owner or engineering leader, with strong communication, collaboration, and mentoring skillsExperience with multiple technology stacks: Cloud Dev, Platforms, Web Dev, Frameworks or service–oriented architectureExperience delivering conversational experiences in chat, voice, or both, including turn and context management, disambiguation and confirmation patterns, and automated-to-human handoffExperience integrating AI into engineering workflows, decision-making, automation, or the software development process itselfAdvanced knowledge experience working with relational databases including development, troubleshooting and performance optimizationSpecification precision and architectural judgment: the ability to define problems rigorously enough that another engineer or an AI agent implements them correctly, and to decide soundly when to solve a problem in code, in instructions, or by delegating to an agentWillingness to work directly with customers in a forward deployed capacity, with the judgment to know when a fast local solution is right and when to hold out for the durable one, and the credibility to communicate capability, limitation, and risk to non-engineersFamiliarity with modern UI frameworks (for example React, Angular, or Vue) and with evaluation, tracing, and prompt or instruction management tooling for LLM applicationsAdvanced command of data structures, algorithms, object-oriented design, design patterns, system design, APIs, and performance optimization10+ years of professional software engineering experience in the SaaS industry, building and operating products at production scaleWorking knowledge of safety, security, and data handling for AI-integrated applications: prompt injection, sensitive-data and secret leakage, over-broad tool access, and unsafe autonomous action, translated into concrete guardrails, least-privilege controls, and monitoringDirect, hands-on experience authoring agentic instructions and prompts, designing AI-driven autonomous workflows, and building the evaluation and testing that verifies non-deterministic behaviorCapability to manage multiple projects with material technical risk across teams and processes; may serve as a functional lead or technical ownerPassion for JavaScript and the Web as a platform, reusability, and componentizationDeep domain experience in high-tech, and familiarity with adjacent regulated industries such as telecommunications, healthcare, financial services, or manufacturing, at a depth sufficient to challenge a requirement rather than only implement itPreferred qualifications:Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience10+ years of experience with Java or a similar OO languageStrong grounding in modern application architecture across cloud, distributed systems, and service-oriented or platform technologies, with solid data modeling and storage fundamentals. Depth matters more than any specific language or frameworkPrior forward deployed, solution engineering, or professional services experience delivering software inside a customer’s environmentAdvanced knowledge with data structures, algorithms, object-oriented design, design patterns and performance/scale considerationsExperience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industryPrompt engineering and evaluation of non-deterministic systems: intent-driven prompt design plus measurable frameworks for response quality, agent behavior, tool-selection accuracy, and regression risk, iterating against evaluation results rather than impressions