Roles And Responsibilities
- AI Engagements: Independently manage end-to-end delivery of AI-led transformation projects across industries, ensuring value realization and high client satisfaction.
- Strategic Consulting & Roadmapping: Identify key enterprise challenges and translate them into AI solution opportunities, crafting transformation roadmaps that leverage RAG, LLMs, and intelligent agent frameworks.
- LLM/RAG Solution Design & Implementation: Architect and deliver cutting-edge AI systems using Python, LangChain, LlamaIndex, OpenAI function calling, semantic search, and vector store integrations (FAISS, Qdrant, Pinecone, ChromaDB).
- Agentic Systems: Design and deploy multi-step agent workflows using frameworks like CrewAI, LangGraph, AutoGen or ReAct, optimizing tool-augmented reasoning pipelines.
- Client Engagement & Advisory: Build lasting client relationships as a trusted AI advisor, delivering technical insight and strategic direction on generative AI initiatives.
- Hands-on Prototyping:
Rapidly prototype PoCs using Python and up-to-date ML/LLM stacks to demonstrate feasibility and business impact.
- Thought Leadership: Conduct market research, stay updated with the latest in GenAI and RAG/Agentic systems, and contribute to whitepapers, blogs, and new offerings.
Essential Skills
- Leadership Quality: Proven track record in leading cross-functional teams and delivering enterprise-grade AI projects with tangible business impact.
- Business Consulting Mindset: Strong problem-solving, stakeholder communication, and business analysis skills to bridge technical and business domains.
- Python & AI Proficiency: Advanced proficiency in Python and popular AI/ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, spaCy, NLTK). Solid understanding of NLP, embeddings, semantic search, and transformer models.
- LLM Ecosystem Fluency: Experience with OpenAI, Cohere, Hugging Face models; prompt engineering; tool/function calling; and structured task orchestration.
- Inde
📌 AI Engineer (India)
🏢 Digile
📍 India