Key Responsibilities
- Design, develop, and deploy end-to-end GenAI use cases and multi-step agentic
workflows spanning the HR hire-to-retire lifecycle (recruiting/TA, onboarding, core HR,
payroll & time, performance management, L&D, compensation & benefits,
career/succession planning, o boarding & retirement)
- Build full stack applications (UI, APIs, backend services) that operationalize AI models
and agents into tools usable by HR teams, managers, and employees
- Architect agentic workflows using orchestration frameworks that plan, reason, and
execute multi-step tasks autonomously, with human-in-the-loop checkpoints where
required
- Integrate LLMs with core HRIS/HCM systems(Workday) and case-management
platforms via APIs and middleware
- Build and maintain Retrieval-Augmented Generation (RAG) pipelines and vector search
to ground AI responses in HR policy, benefits, and compliance content
- Partner with enterprise IT, architecture, security, and data governance teams on
integration design, security review, and infrastructure provisioning
- Work with HR business stakeholders to identify, prioritize, and scope AI/automation
opportunities
- Stand up CI/CD, monitoring, and observability for deployed AI agents and
applications
- Apply responsible AI practices — bias testing, explainability, guardrails, human
oversight — and stay aligned with HR/employment AI compliance requirements
- Produce technical documentation and architecture diagrams; support production issues and iterate post-launch
Technical Skills
- Languages: Python (primary), JavaScript/TypeScript, SQL
- AI / Agentic Frameworks: LangChain, LangGraph, LlamaIndex, Semantic Kernel,
CrewAI, or AutoGen (proficiency in at least two)
- LLM Platforms: OpenAI, Anthropic Claude, Azure OpenAI Service, Google Vertex AI
- RAG / Vector Search: Pinecone, Weaviate, Chroma, Azure AI Search, or pgvector
- Full Stack Development: React/Next.js or Angular (frontend); Node.js or Python
(FastAPI/Django) backend; REST and GraphQL API design
- Cloud & Infrastructure: Azure (preferred, given typical enterprise HR stack), AWS, or
GCP; Docker; Kubernetes
- Automation & Low-Code Platforms: Microsoft Power Platform (Power Automate,
Power Apps, Copilot Studio); UiPath or Automation Anywhere (RPA + AI)
- Integration / Middleware: MuleSoft, Boomi, or Azure Logic Apps for connecting AI
services to enterprise systems
- DevOps: CI/CD (GitHub Actions, Azure DevOps, or Jenkins); Git-based version control
- Databases: PostgreSQL/SQL Server/MySQL; NoSQL (MongoDB, Cosmos DB)
- Security: OAuth2/OIDC, SAML SSO, secure API design, secrets management
Functional / HR Domain Skills (Preferred)
- Working knowledge of the HR hire-to-retire lifecycle end to end: recruiting/talent acquisition, onboarding, core HR & employee data, payroll & time/attendance,
performance management, learning & development, compensation & benefits,
career/succession planning, and o boarding/retirement
- Familiarity with HCM/HRIS platforms such as Workday, SAP SuccessFactors, Oracle HCM Cloud, UKG, or ServiceNow HR Service Delivery — direct integration experience with any of these is a strong plus
- Awareness of the compliance landscape relevant to AI in employment decisions (e.g.,regulations on automated employment decision tools, EU AI Act "high-risk" classification for HR/employment systems, GDPR) and how it shapes responsible AI design
- Ability to translate HR business processes and pain points into technical requirements and solution designs
- Experience supporting change management, user adoption, and stakeholder training for new tools
