Senior AI Enablement Engineer, People

Justworks•New York, NY

7d•$166,000 - $214,000•Onsite

About The Position

This role is for a Senior AI Enablement Engineer, People, who will act as a technical founder embedded within the People function. The ideal candidate has a proven track record of shipping internal tools and AI-powered workflows that are widely adopted. They should be comfortable with both designing AI solutions to address team gaps and developing prototypes. The role requires a proactive, curious individual who is driven by improving people's work lives through technology. This is a hands-on engineering role focused on building AI systems, not just using them. The 'Senior' title reflects organizational reach and impact rather than solely years of experience.

Requirements

6+ years of professional, hands-on builder/software engineering experience.
2+ years of hands-on experience building with LLMs and AI tooling in production: agent frameworks, pipelines, retrieval systems, or AI-integrated workflows that real users depend on.
Familiarity with LLM observability tooling (LangSmith, Datadog LLM monitoring, or equivalent).
Systems-level understanding of data retrieval with comfort working with vector embeddings and combining structured data (e.g., Snowflake tables) with unstructured text.
Strong working knowledge of data privacy standards, including experience building audit trails, role-based permissions, and robust access controls for highly confidential datasets.
Strong communication skills — able to present technical options, trade-offs, and progress to non-technical People and business stakeholders.
Demonstrated ability to work independently in ambiguous, greenfield environments: defining scope, sequencing work, and driving to production without heavy oversight.

Nice To Haves

Familiarity with HR/People systems such as Workday or Greenhouse.

Responsibilities

Drive the technical execution of the People team's AI transformation roadmap, architecting, building, and maintaining intelligent solutions for prioritized operational workflows.
Build agentic workflows, RAG pipelines, and system integrations to scale workflows from 'Human + AI handoffs' to 'AI as a system' maturity.
Scan the external landscape for emerging AI capabilities and market patterns, translating findings into briefs for team experimentation.
Create reproducible blueprints, demos, and guides to ensure long-term operational success and cultivate sustainable AI ownership within the People team.
Partner with the People Analyst and Senior Manager of Data Management & Governance to understand the Snowflake data model, identify trusted and fragile data, and ensure reliable consumption by the AI layer.
Assess the Workday-to-Snowflake pipeline architecture and engineering limitations to ensure AI tools built on it can handle data quirks reliably.
Design evaluation frameworks to measure the accuracy, latency, and real-world utility of AI tools, including hallucination rates, retrieval precision, and user satisfaction.
Implement data privacy and access controls for sensitive people data, including PII handling, role-based access, and audit trails, in coordination with the Data Governance team.
Serve as the primary technical thought partner to the Senior Manager of Strategy Operations, translating People strategy and operational pain points into scoped engineering work.
Collaborate with core engineering and data teams to align on infrastructure, security posture, and standards for enterprise-grade, maintainable People-built systems.
Proactively identify and communicate risks, limitations, and failure modes in AI systems, focusing on fairness, auditability, and responsible deployment in a workforce context.
Stay current on the AI engineering landscape by evaluating new models, frameworks, and tooling, and providing a strong point of view on adoption timing.
Ensure the People team has reliable, production-grade AI tools that reduce manual work, surface better workforce insights, and improve the employee experience.