Lead AI Engineer

Experience: 8–12 Years

Location: Hyderabad (On-site)

Job Summary

As an AI Solutions Specialist , you will design, develop, and deploy enterprise-grade AI solutions using Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI Agents, and cloud AI platforms. You will work closely with AI Engineers, Software Developers, and Solution Architects to build scalable AI applications that solve real-world business problems.

The ideal candidate should have strong hands-on experience building AI-powered applications, integrating LLMs with enterprise systems, and deploying production-ready AI solutions.

Key Responsibilities

• Design, develop, and implement enterprise AI solutions using LLMs, Generative AI, and Agentic AI.
• Build AI applications using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel , or similar.
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.
• Integrate AI services such as OpenAI, Azure OpenAI, Claude, Gemini, or AWS Bedrock into enterprise applications.
• Build and integrate REST APIs and microservices for AI applications.
• Design scalable AI architectures including prompt orchestration, AI workflows, and multi-agent systems.
• Work with structured and unstructured data using SQL, vector databases, and cloud storage.
• Optimize prompt engineering, model performance, latency, accuracy, and cost.
• Deploy AI solutions on cloud platforms such as Azure, AWS, or GCP.
• Collaborate with software engineering teams throughout the AI application lifecycle.
• Monitor AI application performance and continuously improve reliability and response quality.
• Follow AI security, governance, and responsible AI best practices.

Required Technical Skills

Mandatory

• 8–12 years of software engineering or solution development experience.
• 3+ years of hands-on experience in Generative AI and LLM application development .
• Strong experience with OpenAI, Azure OpenAI, Claude, Gemini, or AWS Bedrock APIs .
• Hands-on experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel , or similar AI orchestration frameworks.
• Experience designing and implementing RAG (Retrieval-Augmented Generation) solutions.
• Experience with Vector Databases such as Pinecone, FAISS, ChromaDB, Milvus, or Azure AI Search.
• Strong proficiency in Python .
• Experience with REST APIs , API integrations, and microservices.
• Strong SQL skills.
• Experience with Git, Docker, and CI/CD pipelines.
• Experience deploying AI solutions on Azure, AWS, or GCP .
• Good understanding of prompt engineering, embeddings, tokenization, and model evaluation.

Preferred Skills

• Agentic AI / Multi-Agent Systems
• MCP (Model Context Protocol)
• PromptFlow
• Azure AI Foundry
• Hugging Face
• MLflow
• Kubernetes
• FastAPI
• Streamlit or Gradio
• Redis
• Kafka
• AI observability and monitoring
• Model fine-tuning

Nice to Have

• Experience building AI copilots, AI assistants, or enterprise chatbots.
• Experience with multimodal AI (text, image, speech).
• Experience integrating AI into enterprise applications.
• Knowledge of MLOps and AI deployment best practices.