Staff AI Platform Engineer – HRSD Architect

SmartRecruiters, Inc.; San Diego, Northern (CA, KY); Hybrid; USD 150,000 - 262,000; Full time

Benefits offered by this job

Health plans

401(k) with company match

ESPP

Matching donations

Flexible time away

Family leave programs

Job summary

ServiceNow is seeking a Staff Engineer in HRSD to define the architectural direction for model-driven capabilities across the HR domain and the agentic experiences that interpret employee intent. You will own the architecture, standards, and evaluation infrastructure enabling multiple teams to ship safely.

This role emphasizes production-grade engineering over ML research, focusing on evaluation at scale, responsible data handling, and collaboration to translate business needs into robust

Qualifications

• 7+ years of software engineering with technical direction.
• Experience authoring agentic instructions and prompts.
• Production experience with LLM APIs and orchestration.
• Per-user access enforcement in data handling and tool layers.
• Strong system design, APIs, data modeling and testing.

Responsibilities

• Own AI architecture for the HRSD domain and agent workflows.
• Define decomposition of agents and model orchestration strategies.
• Set policy on HR actions requiring human decisions and constraints.
• Ensure safe, auditable production deployment with safety guarantees.
• Collaborate with product, engineering, design to translate needs.

Skills

Software engineering

Agentic instructions

LLM APIs

System design

On-call incident command

Education

Bachelor's degree in CS or related field

Tools

LLM orchestration

Tool calling

Retrieval-augmented features

Evaluation harnesses

Job description

ServiceNow is seeking a Staff Engineer in HRSD to define the architectural direction for model-driven capabilities across the HR domain and the agentic experiences that interpret employee intent. You will own the architecture, standards, and evaluation infrastructure enabling multiple teams to ship safely.

This role emphasizes production-grade engineering over ML research, focusing on evaluation at scale, responsible data handling, and collaboration to translate business needs into robust