Principal Software Engineer

ServiceNow•San Diego, CA

10d•Hybrid

About The Position

As a Principal Engineer in HRSD, you will set the technical direction for model-driven capability across the HR domain. This includes agentic and conversational experiences that interpret employee, manager, and HR agent intent, reason over profile, case, catalog, policy, and knowledge context, and act on the user's behalf. Your unit of ownership is the architecture, standards, and evaluation infrastructure that allow multiple teams to ship these experiences safely. This role is not an ML research role, nor is it traditional full-stack work. It requires 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

10+ 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 verification evaluations.
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 stacks including Java, JavaScript/TypeScript, React.
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 processes, 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 the autonomy boundary for HR agents, specifying which actions require human decision points and which actions are off-limits (e.g., those affecting pay, employment status, restricted records, or employee relations).
Develop and maintain the shared instruction and tool description surface as a versioned contract with upgrade-safe extension points, deprecation paths, and compatibility guarantees.
Own evaluation as infrastructure, including golden datasets, multi-turn suites, judge calibration, CI gates, and drift detection to enable safe behavior changes.
Extend evaluation coverage to HR-specific failure classes such as 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 mechanisms that work without exposing sensitive HR conversation content.
Establish AI-assisted engineering standards, converting ambiguous problems into testable specifications and defining accountable agent-assisted delivery.
Handle hands-on integration, risky migrations, prototypes, and incident resolution.
Collaborate with product, engineering, and design to co-create scalable AI solutions and translate business needs into technical designs.