Description

Key Responsibilities
🔹 Design, develop, and deploy scalable LLM-powered applications and AI-driven products
🔹 Build AI agents and Agentic AI systems capable of reasoning, planning, and executing complex workflows
🔹 Develop Retrieval-Augmented Generation (RAG) pipelines leveraging proprietary enterprise knowledge bases
🔹 Design and implement MCP servers, AI assistants, and multi-modal AI platforms
🔹 Integrate AI/ML solutions with enterprise systems, APIs, cloud platforms, and data ecosystems
🔹 Develop prompt engineering strategies, model evaluation frameworks, and AI guardrails
🔹 Optimize LLM performance through orchestration, fine-tuning approaches, and prompt engineering
🔹 Build MLOps and LLMOps pipelines for monitoring, governance, evaluation, and continuous improvement
🔹 Collaborate with business, technology, and data teams to deliver innovative AI solutions
Required Skills
✅ Python Programming
✅ Large Language Models (LLMs)
✅ Generative AI
✅ Agentic AI
✅ Retrieval-Augmented Generation (RAG)
✅ Model Context Protocol (MCP)
✅ LangChain
✅ LangGraph
✅ Hugging Face
✅ Vector Databases
✅ Prompt Engineering
✅ Embeddings & Model Evaluation
✅ API Development
✅ AI Tools:
• Claude Code
• Codex
• Cursor
• GitHub Copilot
Preferred Skills
⭐ AWS, Azure, or GCP Cloud Platforms
⭐ Snowflake
⭐ LlamaIndex
⭐ AutoGen
⭐ CrewAI
⭐ Semantic Kernel
⭐ Fine-Tuning LLMs (LoRA, PEFT)
⭐ MLOps / LLMOps
⭐ AI Governance & Observability
⭐ Java and JavaScript
Qualifications
🎓 Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a related field
🎯 Hands-on experience building and deploying production-grade AI applications
🎯 Strong understanding of enterprise AI architecture and modern AI frameworks
🎯 Passion for innovation, AI technologies, and solving complex business challenges

Key Skills

Education

Bachelor's or Master's degrees