Technical Lead
HCLTech
Technical Lead
About this role
Job Summary
Mandatory/Required SkillsStrong hands-on experience in Generative AI / LLM Engineering.Expertise in building Agentic AI systems using LangGraph, LangChain, CrewAI, or AutoGen.Experience with RAG / Graph-RAG architectures and vector databases (Pinecone, pgvector, OpenSearch, Neo4j, etc.).Strong Python backend development skills with FastAPI, async programming, APIs, and inference services.Hands-on experience with OpenAI, Anthropic, Gemini, Hugging Face, or similar LLM ecosystems.Experience in prompt engineering, fine-tuning, LoRA/PEFT, embeddings, semantic search, and agent memory frameworks.Strong cloud exposure in AWS/Azure/GCP with MLOps/LLMOps tools like MLflow.Experience working on production-scale AI/ML applications.Good understanding of Deep Learning frameworks such as PyTorch or TensorFlow.Strong communication and stakeholder management skills.Good to Have SkillsMultimodal AI experience (text, image, audio, graph-based AI systems).Experience with Graph-RAG and Knowledge Graphs.Exposure to Responsible AI / AI Governance frameworks.Experience with Databricks, Bedrock, Vertex AI, Azure OpenAI.Traditional ML/statistical modeling knowledge.Experience leading teams or architecting enterprise AI platforms.
Key Responsibilities
Mandatory/Required SkillsStrong hands-on experience in Generative AI / LLM Engineering.Expertise in building Agentic AI systems using LangGraph, LangChain, CrewAI, or AutoGen.Experience with RAG / Graph-RAG architectures and vector databases (Pinecone, pgvector, OpenSearch, Neo4j, etc.).Strong Python backend development skills with FastAPI, async programming, APIs, and inference services.Hands-on experience with OpenAI, Anthropic, Gemini, Hugging Face, or similar LLM ecosystems.Experience in prompt engineering, fine-tuning, LoRA/PEFT, embeddings, semantic search, and agent memory frameworks.Strong cloud exposure in AWS/Azure/GCP with MLOps/LLMOps tools like MLflow.Experience working on production-scale AI/ML applications.Good understanding of Deep Learning frameworks such as PyTorch or TensorFlow.Strong communication and stakeholder management skills.Good to Have SkillsMultimodal AI experience (text, image, audio, graph-based AI systems).Experience with Graph-RAG and Knowledge Graphs.Exposure to Responsible AI / AI Governance frameworks.Experience with Databricks, Bedrock, Vertex AI, Azure OpenAI.Traditional ML/statistical modeling knowledge.Experience leading teams or architecting enterprise AI platforms.
Skill Requirements
Mandatory/Required SkillsStrong hands-on experience in Generative AI / LLM Engineering.Expertise in building Agentic AI systems using LangGraph, LangChain, CrewAI, or AutoGen.Experience with RAG / Graph-RAG architectures and vector databases (Pinecone, pgvector, OpenSearch, Neo4j, etc.).Strong Python backend development skills with FastAPI, async programming, APIs, and inference services.Hands-on experience with OpenAI, Anthropic, Gemini, Hugging Face, or similar LLM ecosystems.Experience in prompt engineering, fine-tuning, LoRA/PEFT, embeddings, semantic search, and agent memory frameworks.Strong cloud exposure in AWS/Azure/GCP with MLOps/LLMOps tools like MLflow.Experience working on production-scale AI/ML applications.Good understanding of Deep Learning frameworks such as PyTorch or TensorFlow.Strong communication and stakeholder management skills.Good to Have SkillsMultimodal AI experience (text, image, audio, graph-based AI systems).Experience with Graph-RAG and Knowledge Graphs.Exposure to Responsible AI / AI Governance frameworks.Experience with Databricks, Bedrock, Vertex AI, Azure OpenAI.Traditional ML/statistical modeling knowledge.Experience leading teams or architecting enterprise AI platforms.
Other Requirements
Mandatory/Required SkillsStrong hands-on experience in Generative AI / LLM Engineering.Expertise in building Agentic AI systems using LangGraph, LangChain, CrewAI, or AutoGen.Experience with RAG / Graph-RAG architectures and vector databases (Pinecone, pgvector, OpenSearch, Neo4j, etc.).Strong Python backend development skills with FastAPI, async programming, APIs, and inference services.Hands-on experience with OpenAI, Anthropic, Gemini, Hugging Face, or similar LLM ecosystems.Experience in prompt engineering, fine-tuning, LoRA/PEFT, embeddings, semantic search, and agent memory frameworks.Strong cloud exposure in AWS/Azure/GCP with MLOps/LLMOps tools like MLflow.Experience working on production-scale AI/ML applications.Good understanding of Deep Learning frameworks such as PyTorch or TensorFlow.Strong communication and stakeholder management skills.Good to Have SkillsMultimodal AI experience (text, image, audio, graph-based AI systems).Experience with Graph-RAG and Knowledge Graphs.Exposure to Responsible AI / AI Governance frameworks.Experience with Databricks, Bedrock, Vertex AI, Azure OpenAI.Traditional ML/statistical modeling knowledge.Experience leading teams or architecting enterprise AI platforms.
Frequently Asked Questions
Is the salary disclosed for the Technical Lead position at HCLTech?
The salary for this Technical Lead role at HCLTech is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Technical Lead position at HCLTech located?
This Technical Lead role at HCLTech is based in Pune, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
How do I apply for the Technical Lead position at HCLTech?
Click the "Apply Now" button on this page. You will be redirected to HCLTech's official application portal hosted on successfactors where you can submit your application directly.
When was the Technical Lead job at HCLTech posted?
This Technical Lead position at HCLTech was posted on Sep 1, 2026. Apply as soon as possible — early applications are often reviewed first.
Technical Lead
HCLTech
You'll be redirected to HCLTech's official application page on successfactors.