Senior Engineer-LLM

Summary

Join IQEQ, a leading service provider to the alternative asset industry, as a Lead - AI Engineer. You will spearhead AI strategy, architecture, and development, leveraging expertise in LLMs, RAG, multi-agent AI frameworks, vector databases, and AI security. This role involves leading a team in building scalable AI applications, focusing on LLM-driven solutions, AI-powered automation, and Conversational AI chatbots. You will be responsible for defining AI system architectures, collaborating with product teams, researching cutting-edge AI innovations, and developing and optimizing AI workflows. The position also requires expertise in API and backend engineering, including developing RESTful APIs, working with databases, and designing scalable microservices architectures. This opportunity offers competitive salary, leadership opportunities, and cutting-edge projects.

Requirements

• Expertise in LLMs, Advanced RAG techniques, and knowledge retrieval using vector databases (FAISS, Quadrant, Chroma)
• Hands-on experience with multi-agent AI frameworks like AutoGen for intelligent automation
• Experience in deep learning using TensorFlow, PyTorch, and fine-tuning open-source LLMs
• Hyderabad, India (Remote/Hybrid Available)
• 9+ Years (6+ Years in Data Science & AI)
• Full-time

Responsibilities

• Lead & mentor a team of AI engineers and data scientists
• Define AI system architectures integrating LLMs, multi-agent AI, and secure AI solutions
• Collaborate with product teams and stakeholders to design AI-driven applications
• Research and implement cutting-edge AI innovations in retrieval-augmented generation (RAG) and LLM fine-tuning
• Develop and optimize AI workflows using LangChain, LlamaIndex, and LangGraph for real-time AI-driven applications
• Implement LLM security frameworks (Guardrails, LLM Guard, AI Red Teaming) to ensure ethical AI usage
• Develop Conversational AI chatbots for enterprise applications using LLMs and NLP frameworks
• Develop and optimize RESTful APIs using FastAPI
• Work with relational & NoSQL databases for AI-driven applications
• Design and implement scalable microservices architectures for AI model deployment
• Integrate and deploy LLMs for real-time AI-powered solutions with optimized response times

Preferred Qualifications

• Experience with AWS, Azure for scalable AI deployments
• Familiarity with Docker & Kubernetes for containerized AI solutions
• Exposure to CI/CD pipelines for automated AI model deployment

Benefits

• Lead AI innovation in LLMs, RAG, and AI security
• Drive AI-powered transformation across industries
• Competitive salary, leadership opportunities, and cutting-edge projects