Senior AI Enablement Engineer (People)

Join Justworks as a Senior AI Enablement Engineer, where you'll drive the technical execution of our AI transformation roadmap within the People function. You'll build intelligent solutions, partner with data management teams, and ensure responsible AI deployment. This role requires a strong background in software engineering, AI systems, and data privacy standards. Enjoy benefits like paid volunteer work, parental leave, and extensive learning opportunities.

• Conduire l'exécution technique de la feuille de route de transformation de l'IA de l'équipe People, en architecturant, construisant et maintenant des solutions intelligentes.
• Collaborer avec l'analyste People et le responsable senior de la gestion des données pour comprendre le modèle de données existant et identifier ce qui est fiable.
• Servir de partenaire technique principal pour traduire la stratégie People et les points de douleur opérationnels en travaux d'ingénierie.

• 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
• 6+ years of professional, hands-on builder/software engineering experience
• Demonstrated ability to work independently in ambiguous, greenfield environments: defining scope, sequencing work, and driving to production without heavy oversight
• Familiarity with HR/People systems such as Workday or Greenhouse is a meaningful plus, but not required
• 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 communication skills — able to present technical options, trade-offs, and progress to non-technical People and business stakeholders
• 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
• Strong working knowledge of data privacy standards, including experience building audit trails, role-based permissions, and robust access controls for highly confidential datasets