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Generative AI Engineer

Actively Reviewing the Applications

HCLTech

India, Maharashtra, Nagpur Full-Time On-site
Posted 1 day ago Apply by May 24, 2026

Job Description

Exp-5+ years

Location-Nagpur


We are looking for a Generative AI Developer who can design and implement GenAI-powered features, develop intelligent AI agents, and deploy end-to-end GenAI solutions leveraging cloud AI services. This role focuses on solution integration and orchestration, not model training, and requires hands-on experience with platforms like GitHub Copilot, GHCP, and enterprise-grade AI ecosystems.

Key Responsibilities

  • Develop GenAI-driven features for applications and workflows.
  • Build and integrate AI agents for automation and conversational interfaces.
  • Deploy GenAI solutions (not raw models) into production environments ensuring scalability and security.
  • Work with cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI) for model hosting and orchestration.
  • Implement prompt engineering, context management, and guardrails for safe AI usage.
  • Collaborate with product teams to design user-centric AI experiences.
  • Optimize solutions for cost, latency, and compliance.
  • Stay updated on GenAI frameworks, Copilot integrations, and emerging best practices.

Required Skills & Qualifications

  • Education: Bachelor’s in Computer Science, AI/ML, or related field.
  • Experience: 2–3 years in AI/ML development, with at least 1 year in GenAI solution deployment.
  • Strong proficiency in Python and API integration.
  • Hands-on experience with GitHub Copilot, GHCP, and AI-assisted development tools.
  • Familiarity with Strands Agents framework, CrewAI, Azure's Agents-framework, GCP's Agent Development Kit, and certification in prompt engineering
  • Experience deploying solutions using Azure AI, AWS, or GCP.
  • Understanding of security, compliance, and ethical AI principles.

Preferred Skills

  • Knowledge of RAG pipelines and vector databases.
  • Experience with workflow automation using AI agents.
  • Exposure to CI/CD, Docker, and Kubernetes for solution deployment.
  • Familiarity with enterprise AI governance and cost optimization strategies.

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