AI Engineer - HR

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

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