Key Responsibilities :

- Lead end-to-end delivery of Generative AI solutions for clients, particularly in manufacturing and administrative domains.

- Architect and implement AI/ML models using advanced techniques in NLP, LLMs (Large Language Models), and generative technologies tailored to specific industry use cases.

- Engage directly with clients to understand business needs, challenges, and objectives, and translate them into actionable technical solutions.

- Mentor and guide junior consultants and technical teams in best practices for GenAI development, deployment, and lifecycle management.

- Collaborate cross-functionally with data engineers, product managers, DevOps, and business stakeholders to ensure smooth integration and deployment of AI solutions.

- Ensure solutions are robust, scalable, secure, and compliant with industry and organizational standards.

- Stay current with the latest GenAI trends, tools, frameworks, and research to continuously drive innovation and elevate solution quality.

- Support pre-sales, proposals, and client pitches as a technical SME in GenAI, contributing to solution design, estimations, and presentations.

Required Skills & Qualifications :

- Minimum 4 years of experience in AI/ML engineering, with at least 12 years focused on GenAI technologies.

- Proven experience in designing and delivering LLM-powered solutions (e.g., using OpenAI, Hugging Face Transformers, LangChain, RAG architecture, etc.).

- Proficient in Python, with experience using AI/ML libraries such as TensorFlow, PyTorch, spaCy, or similar.

- Strong experience in NLP, prompt engineering, and working with generative models (e.g., GPT, LLaMA, Claude).

- Deep understanding of cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

- Excellent communication and stakeholder engagement skills, with the ability to interact with both technical and non-technical audiences.

- Ability to lead projects, mentor team members, and collaborate in a fast-paced, agile environment.

Preferred Qualifications :

- Experience in industry-specific GenAI use cases in manufacturing, supply chain, or enterprise productivity tools.

- Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG (Retrieval-Augmented Generation) pipelines.

- Exposure to MLOps and CI/CD pipelines for model deployment and monitoring.

- Contributions to open-source GenAI projects or published research work.