AI Engineer

- Design, develop, and deploy enterprise-grade applications powered by Large Language Models (LLMs) and foundation models.

- Build Retrieval-Augmented Generation (RAG) solutions leveraging vector databases, enterprise knowledge repositories, and GraphRAG architectures.

- Develop conversational AI assistants, enterprise copilots, intelligent chatbots, and workflow automation solutions.

- Implement advanced prompt engineering techniques including Chain of Thought (CoT), ReAct, Self-Reflection, Multi-Step Reasoning, and Tool Calling.

- Design and develop multi-agent AI systems capable of autonomous planning, reasoning, task decomposition, and execution.

- Build agent orchestration frameworks integrating enterprise applications, APIs, and external services.

- Implement agent memory management, communication protocols, and human-in-the-loop workflows.

- Develop scalable AI services, APIs, and reusable AI platform components for enterprise deployments.

- Integrate AI solutions with enterprise platforms including CRM, ERP, Supply Chain, Data Warehouses, and Knowledge Management systems.

- Design and implement AI governance, monitoring, observability, and evaluation frameworks.

- Evaluate AI applications for relevance, groundedness, hallucination, safety, accuracy, and overall performance.

- Build automated evaluation pipelines, testing frameworks, and continuous model validation processes.

- Optimize inference performance, latency, scalability, token utilization, and infrastructure costs.

- Collaborate with Product, Engineering, Data Science, and Business teams to deliver production-ready AI solutions.

- Stay updated with emerging trends in Generative AI, Agentic AI, LLMs, and enterprise AI platforms.