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Enterprise AI Engineer - Modernization

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OptiSol Business Solutions

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Location:
India , Chennai, Madurai

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

We’re hiring a Generative AI Engineer for our AI-powered modernization platform (iBEAM). Role involves building RAG pipelines, AI agents, LLM integrations & scalable Python services for enterprise transformation use cases.

Job Responsibility:

  • Design, develop, and deploy Generative AI–powered software solutions
  • Build robust, scalable Python services integrating Large Language Models (LLMs)
  • Craft and optimize advanced prompts to enforce accuracy, tone, formatting, and guardrails
  • Fine-tune and adapt LLMs for domain-specific and business-critical use cases
  • Architect and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines
  • Develop autonomous and semi-autonomous AI agents
  • Integrate LLMs with external APIs, databases, and computation engines
  • Evaluate and monitor model behavior to detect hallucinations, drift, and quality regressions
  • Write production-grade, modular Python code and participate in code reviews
  • Stay current with emerging research, tools, and best practices in Generative AI

Requirements:

  • Hands-on experience working with foundation models such as GPT-4, Claude, Llama 3, or Mistral to build real-world AI applications
  • Strong prompt engineering skills including Chain-of-Thought, Few-Shot Prompting, and Tree-of-Thought reasoning techniques
  • Ability to design and optimize prompts to improve response accuracy, reduce latency, and control token cost
  • Experience creating system prompts with structured outputs (JSON or schema-based) and implementing safety guardrails
  • Understanding of LLM data preparation including dataset cleaning, formatting & tokenization
  • Exposure to model adaptation or fine-tuning workflows using modern ML pipelines
  • Working knowledge of machine learning frameworks such as PyTorch or TensorFlow
  • Hands-on experience designing and implementing end-to-end Retrieval-Augmented Generation (RAG) pipelines
  • Exposure to vector databases such as Pinecone, Weaviate, Milvus, or Qdrant
  • Strong understanding of embeddings, semantic search, and re-ranking strategies
  • Experience building AI agents or agentic workflows using frameworks such as LangChain, LangGraph, or AutoGPT
  • Ability to implement tool or function calling that enables LLMs to interact with external APIs, databases, or services
  • Primary Language: Python (expert level)
  • Libraries & Frameworks: Hugging Face Transformers, LangChain, LangGraph, LlamaIndex, OpenAI APIs
  • Development & Deployment: Jupyter Notebooks, Docker, FastAPI

Nice to have:

  • Experience deploying AI-powered systems in production environments
  • Familiarity with MLOps / LLMOps practices
  • Exposure to enterprise-scale platforms or developer tooling

Additional Information:

Job Posted:
March 22, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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