Staff Software Engineer

ServiceNow•Santa Clara, CA

10d•$166,500 - $291,400•Hybrid

About The Position

As a Staff Engineer in HRSD, you will set the technical direction for model-driven capability across the HR domain, focusing on agentic and conversational experiences that interpret employee, manager, and HR agent intent. You will reason over profile, case, catalog, policy, and knowledge context, and act on the user's behalf. Your unit of ownership will be the architecture, standards, and evaluation infrastructure that enable multiple teams to ship these experiences safely. This role is not focused on ML research or traditional full-stack development with deterministic logic. Instead, it emphasizes engineering natural language logic (instructions, prompts, context, tool descriptions, guardrails) with the same discipline as code, and establishing correctness through large-scale evaluation due to probabilistic behavior.

Requirements

7+ years of software engineering experience with a record of technical direction adopted beyond your immediate team.
Direct, hands-on experience authoring agentic instructions and prompts, designing autonomous workflows, and building the evaluation that verifies them.
Production experience with LLM APIs, retrieval-grounded features, agent orchestration, tool and function calling, and structured output enforcement, including at least one model or orchestration migration carried through production.
Entitlement-aware data handling: per-user access enforcement in retrieval and tool layers, scope separation between roles, and handling of restricted records under audit.
Evaluation experience used by engineers other than yourself: dataset curation, judge calibration, CI gating, drift detection.
Strong command of system design, APIs, data modeling, and testing across front-end, server-side, and relational data work with a high-quality mindset.
Effective, accountable use of AI coding assistants and agents.
On-call and incident-command experience on customer-facing systems, including ownership of systemic fixes.
Experience in software stack including Java, JavaScript/TypeScript, React and demonstrated ability to quickly learn new tools and frameworks.
Bachelor's degree in CS, software engineering, or a related technical field, or equivalent practical experience.

Nice To Haves

HR domain depth: case management, employee journey and lifecycle, or payroll/benefits/leave/absence sufficient to set requirements.
Integration with core HR, payroll, or benefits systems of record, including reconciliation and eventual-consistency patterns.
Contribution in a Forward deployment model to champion customer adoption.

Responsibilities

Set the technical direction for AI architecture within the HR domain, including agent decomposition and composition, reasoning locations, context assembly and bounding, tool exposure, and autonomy delegation.
Own multi-release calls related to model selection and migration, orchestration approach, build-versus-adopt decisions, and the associated cost/latency/quality tradeoffs.
Define and enforce the autonomy boundary for HR actions, determining which actions agents can take, which require human decision points, and which should not be attempted. Build mechanisms to make constraints structural, especially for actions involving pay, employment status, restricted records, or employee relations.
Own the shared instruction and tool description surface, treating it as a versioned contract with upgrade-safe extension points, deprecation paths, and compatibility guarantees for customer configuration and extension.
Own evaluation as infrastructure, including golden datasets, multi-turn suites, judge calibration, CI gates, and drift detection to allow teams to change behavior safely. Extend coverage to HR-specific failure classes like access-boundary violations, cross-scope leakage, and jurisdictional/policy-variant correctness.
Ensure production quality and safety through observability for containment, hallucination rate, tool-selection error, unsafe action, and injection vectors. Design diagnosis that works without exposing sensitive HR conversation content.
Establish AI-assisted engineering standards for the domain, including specification standards, review expectations, and verification harnesses, ensuring accountable agent-assisted delivery.
Perform hands-on work for critical integrations, risky migrations, architectural prototypes, and unblocking complex incidents.
Collaborate with product, engineering, and design teams to co-create scalable AI solutions and translate business needs into robust technical designs.