HR AI Projects

We are looking for a highly motivated fresh graduate to support AI-led HR transformation initiatives.

The role will involve understanding HR processes, identifying opportunities for automation and intelligent intervention, and determining whether a use case is best addressed through AI Agents, Generative AI, Chatbots, RPA, Machine Learning or traditional technology solutions.

Candidates should be able to understand the business/process problem first and then identify the most appropriate technology solution.

What we are looking for

Candidate Requirements:

Qualification:

Candidates pursuing or recently completing a degree in Computer Science, AI, ML, Data Science, IT, Software Engineering, Electronics or related disciplines.

Candidate with with strong hands-on AI/automation projects

Freshers, Recent Graduates, or Final-Year Students.

Technical Skills

Hands-on exposure to AI/ML and Generative AI.

Experience building AI Agents, Chatbots or Bots

Python or another programming language  Understanding of LLMs, APIs and system integrations

Basic Machine Learning knowledge.

Exposure to RPA/automation tools such as UiPath, Power Automate or Automation Anywhere

Understanding of prompt engineering and LLM workflows.

SQL/database knowledge is an advantage.

Experience building AI Agents / Agentic AI workflows.

Exposure to frameworks such as LangChain, LangGraph, CrewAI, AutoGen or similar frameworks.

Experience integrating LLMs with APIs/tools.

Academic or personal projects involving AI, automation or ML.

Key Responsibilities

Understand HR processes across areas such as HR Operations, Recruitment, Employee Experience, Payroll, Learning, Benefits and Attendance.

Analyse process flows, dependencies, data, decision points and manual interventions.

Identify opportunities to simplify, digitise, automate or intelligently automate HR processes.

Evaluate the appropriate technology approach — RPA, AI Agents, GenAI, Chatbots, ML, APIs or traditional workflows.

Develop AI agents, bots and automation solutions, including Proofs of Concept (PoCs).

Work with LLMs, APIs, automation platforms and AI/ML technologies.

Support data analysis, model development and validation of AI outputs where required. Challenge existing processes and design improved future-state processes.

Test solutions, identify edge cases and support pilot implementation.

Document use cases, solution approaches, learnings and recommendations.