Distinguished Platform Engineer (AI)

Quick Facts

• Role: Distinguished Engineer setting technical direction for an AI-enabled HR platform
• Focus: Model-driven capability, agentic/conversational experiences, architecture standards, and evaluation infrastructure

Description

Own the architecture, standards, and evaluation infrastructure that enable multiple teams to ship safe AI agent and conversational experiences across the HR domain. You will not train foundation models; instead, you will engineer load-bearing prompt/instruction logic and establish correctness through large-scale evaluation, observability, and CI/drift gates. Responsibilities span AI architecture, autonomy boundaries, tool/instruction surfaces, entitlement-aware data handling, production safety, and incident-driven engineering fixes.

Responsibilities

• Define AI architecture for the HR domain (reasoning, context assembly/bounds, tool exposure, delegated autonomy)
• Own multi-release model selection/migration and orchestration approach, including build-versus-adopt and cost/latency/quality tradeoffs
• Set and enforce autonomy boundaries and human-in-the-path constraints for restricted HR actions
• Maintain a versioned, upgrade-safe shared instruction and tool description contract for customers
• Build evaluation infrastructure: golden datasets, multi-turn suites, judge calibration, CI gates, and drift detection, including HR-specific failure-class coverage
• Ensure production quality and safety via observability for hallucinations, unsafe actions, and injection vectors
• Convert ambiguous problems into testable specifications and define delivery/specification standards
• Provide hands-on engineering for hard integrations, risky migrations, and prototypes that resolve architectural debates
• Collaborate with product, engineering, and design to translate business needs into robust technical designs

Requirements

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

Benefits

• Base pay range: $279,100–$488,400 plus equity (when applicable), variable/incentive compensation, and benefits