Senior Staff Applications Development Engineer

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, Service Now is the AI control tower for business reinvention. Our Service Now AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better.

We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people.

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.

To be successful in this role you have:
Experience 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 industry. 10+ years of professional software engineering experience in the SaaS industry, building and operating products at production scale. A demonstrated track record of building, shipping, and operating production software,…