Department

People (Embedded Engineering Model)

Reporting Structure: This role uses an embedded model designed for maximum technical growth and business impact. Day-to-day business requirements, vision, and prioritization are directed by the People Team leadership. Technical mentorship, code reviews, and engineering career guardrails are provided via a dedicated Engineering Manager partner.

Who You Are

Reporting to the Senior Manager, People Strategy Operations, the Senior AI Enablement Engineer, People, is a technical founder embedded within the People function. 

You have a track record of shipping internal tools and AI-powered workflows that people actually use. You're as comfortable mapping a team’s AI gaps and designing a solution as you are vibe-coding a working prototype with an AI agent. You're insatiably curious and never satisfied with the status quo — you operate with urgency and agency, center the customer in every decision, and make every team you join better. You think in systems, move fast, and know how to bring people along without manufacturing consensus. You don’t need to come from HR. You need to care about building tools that make people’s work lives better.

This is a true engineering role. We are looking for someone with production experience shipping AI systems — not someone who uses AI tools, but someone who builds them. Senior here means senior by organizational reach and shipped impact, not by years of CS experience. 

Your Success Profile

What You Will Work On

• Building the Core AI & Automation Layer (~50%)
  • Drive the technical execution of the People team's AI transformation roadmap—architecting, building, and maintaining intelligent solutions around our prioritized operational workflows.
  • Build agentic workflows, RAG pipelines, and system integrations required to scale workflows from ‘Human + AI handoffs’ to ‘AI as a system’ level maturity.
  • Scan externally for emerging AI capabilities and market patterns; translate signal into written briefs that inform what the team experiments on next.
  • Embed long-term operational success by creating reproducible blueprints, demos, and guides that naturally transfer expertise and cultivate sustainable AI ownership across the People team.
• Data Layer & AI Reliability (~25%)
  • Partner with the People Analyst and Senior Manager of Data Management & Governance to deeply understand the existing Snowflake data model to identify what is trusted, what is fragile, and what the AI layer can reliably consume.
  • Assess the custom Workday-to-Snowflake pipeline to understand its architecture and engineering limitations, ensuring any AI tools built on top of it are designed to 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, to iterate based on those signals.
  • Implement data privacy and access controls appropriate to highly sensitive people data, including PII handling, role-based access, and audit trails in close coordination with the Data Governance team.
• Technical Partnership & Responsible AI (~25%)
  • Serve as the primary technical thought partner to the Senior Manager of Strategy Operations to translate People strategy and operational pain points into scoped, sequenced engineering work.
  • Collaborate with core engineering and data teams to align on infrastructure, security posture, and standards to ensure People-built systems are enterprise-grade and maintainable by others. 
  • Proactively surface risks, limitations, and failure modes in AI systems before they impact employees by building with an explicit lens on fairness, auditability, and responsible deployment in a workforce context.
  • Stay current on the AI engineering landscape by evaluating new models, frameworks, and tooling as they become relevant while bringing a strong point of view on when to adopt versus wait. 

In this role, success looks like: the People team has reliable, production-grade AI tools that reduce manual work, surface better workforce insights, and make it easier for every Justworks employee to navigate their experience — built and owned by an engineer who takes full accountability for what they ship. 

How You Will Do Your Work

Success in this role is defined not only by what you ship, but how you ship it. Core capabilities include:

• Technical Craft — writing clean, tested, maintainable code; making sound architectural decisions; and building systems that hold up in production, not just in a demo.
• Problem Translation — taking ambiguous People team needs and converting them into well-scoped technical solutions with clear success criteria and measurable outcomes.
• Plans and Aligns — breaking down complex builds into sequenced milestones; communicating progress and blockers proactively to non-technical stakeholders without being asked.
• Initiative and Motivation — identifying what needs to be built before being asked, and driving it from whiteboard to production without heavy supervision.
• Teamwork and Communication — documenting systems thoroughly, collaborating across engineering and People, and explaining technical trade-offs in plain language to people who don’t write code.

In addition, all Justworkers focus on aligning their behaviors to our core values, known as COGIS:

• Camaraderie — Day-to-day, you can be seen working together toward a higher purpose. You like to have fun. You’re an active listener, treat people respectfully, and have a strong desire to know and help others.
• Openness — Your default is to be open. You’re willing to share information, understand other perspectives, and consider new possibilities. You’re curious, ask open questions, and are receptive to thoughts and feedback from others.
• Grit — You demonstrate grit by having the courage to commit and persevere. You’re committed, earnest, and dive in to get the job done well with a positive attitude.
• Integrity — Simply put, do what you say and say what you’ll do. You’re honest and forthright, have a strong moral compass, and strive to match your words with your actions while leading by example.
• Simplicity — Be like Einstein: “Everything should be made as simple as possible, but no simpler.”

Qualifications

• 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): you instrument what you build and use signal to improve it
• Systems-level understanding of data retrieval with comfort working with vector embeddings and combining structured data, such as Snowflake tables, with unstructured text to power intelligent, context-aware internal tools. 
• Strong working knowledge of data privacy standards, including experience building audit trails, role-based permissions, and robust access controls for highly confidential datasets.
• Familiarity with HR/People systems such as Workday or Greenhouse is a meaningful plus, but not required.
• 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.

The base wage range for this position based in our New York City Office is targeted at $166,000.00 - $214,000.00 per year.