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Agentic AI Engineer

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Onsite

Agentic AI Engineer

HCLTech

Agentic AI Engineer

Skills

Google Cloud PlatformSQL QueriesDeep LearningPythonPyTorchTensorFlowMachine LearningAIAWSNLP / Natural Language ProcessingAzure

8 days ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

15 October 2026

What they need


Role: Agentic AI Engineer

Location: Chennai/Bangalore/Hyderabad/Noida/pune

Notice: Immediate to 30 days

Experience: 5-15 Years

Job Summary

The Agentic AI Engineer will be responsible for designing, developing, and deploying AI-driven solutions leveraging large language models (LLMs), diffusion models, and other generative frameworks. The role involves collaborating closely with data scientists, software engineers, and business teams to create intelligent, context-aware applications that enhance automation, creativity, and decision-making across the enterprise.

Key Responsibilities

Design, fine-tune, and deploy large language models (LLMs) and other generative models for specific business use cases.

  • Build and optimize prompt engineering and model interaction strategies for improved output accuracy and relevance.

  • Develop APIs, pipelines, and integrations to embed generative AI capabilities into products and workflows.

  • Collaborate with data engineers to ensure high-quality, domain-relevant datasets for model training and evaluation.

  • Implement responsible AI principles, including bias mitigation, explainability, and data governance.

  • Monitor model performance and continuously refine models through feedback loops and retraining.

  • Stay up to date with emerging trends in AI research, frameworks (e.g., LangChain, Hugging Face, OpenAI API), and open-source tools.

  • Contribute to internal knowledge sharing and best practices for scalable AI deployment.

Skill Requirements

o Proficiency in Python and frameworks such as PyTorch or TensorFlow.

o Experience in SQL, Machine Learning, Big Dat and other Databases.

o Experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and vector databases (Pinecone, FAISS, Weaviate).

o Familiarity with prompt engineering, model fine-tuning, and reinforcement learning from human feedback (RLHF).

o Strong understanding of NLP, deep learning, and data pipeline design.

o Exposure to cloud platforms (AWS, Azure, GCP) and MLOps tools for model deployment.

o Strong problem-solving and analytical thinking.

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