Role summary

You will own AI in the Flow of Work” and find where AI can change how HCLSoftware works, then build it. You start with IT, modernizing and automating its workflows with AI, then extend to other functions and org-wide processes. Your work spans the four layers of our enterprise intelligence stack: data, semantics, agents, and the employee interface.

What you will do

- Find the opportunities. Map workflows with process owners, size the friction, and keep a ranked backlog of AI use cases, each with a value case.
- Design and build. Prototype rapid, then deliver agents and automations on approved enterprise AI platforms, connected to the data and systems they need.
- Ship and scale. Take proven use cases to production, drive adoption and reuse patterns across functions.
- Measure. Baseline each workflow before changing it. Report time saved, automation rate, adoption, and cost.

How success is measured

- 3 months: first AI use case in pilot, with baselines for the outcomes it is meant to improve.
- 6 months:



multiple IT workflows modernized in production, each with a measured improvement in time, effort, or experience.
- 12 months: AI use cases live beyond IT, with growing adoption at a sustainable cost.

Out of scope AI governance and data policy (Security). Identity, SSO, and AI platform infrastructure (Engineering)

Required

- 5+ years building automation, integrations, or internal tools in IT, digital workplace, or enterprise applications.
- Hands-on experience with Claude, ChatGPT Enterprise, Gemini, or Copilot, including building agents or assistants.
- Code and data: Python or JavaScript/TypeScript, REST APIs, and SQL.
- Able to turn a loose process into a problem statement and a working prototype, and present it to non-technical stakeholders.
- Preferred: background in IT service management or onboarding, MCP and workflow orchestration, and experience measurement.

📌 AI Enablement Engineer (Bengaluru)
🏢 HCLTech
📍 Bengaluru