AI Engineer - HR

Revvity; Thane; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Revvity is seeking an expert AI engineer to design, build, and deploy end-to-end GenAI solutions spanning recruiting, onboarding, core HR, payroll, and performance management. You will architect multi-step agentic workflows, integrate LLMs with Workday and other HR systems, and create scalable full-stack tools for HR teams and employees.

The role requires strong experience in AI frameworks, LLM platforms, and cloud infrastructure, with a focus on responsible AI and compliance.

Qualifications

• Integrate LLMs with 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.

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, oboarding & 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
• 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

Skills

Python

JavaScript/TypeScript

SQL

LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI

AutoGen

OpenAI

Anthropic Claude

Azure OpenAI Service

Google Vertex AI

Pinecone

Weaviate

Chroma

Azure AI Search

pgvector

React/Next.js

Angular

Node.js

FastAPI/Django

REST

GraphQL

Azure

AWS

GCP

Docker

Kubernetes

Power Platform

Power Automate

Power Apps

Copilot Studio

UiPath

Automation Anywhere

MuleSoft

Boomi

Azure Logic Apps

GitHub Actions

Azure DevOps

Jenkins

Git

PostgreSQL

SQL Server

MySQL

MongoDB

Cosmos DB

OAuth2/OIDC

SAML SSO

secure API design

secrets management

Job description

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, oboarding & 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
• 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

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 oboarding/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