Technology Lead | Enterprise Content Management | IBM Watson

Pay Rate Range: $ 58.57 - 60.29/hr on W2Must Have Skills:Core AI & GenAI Expertise· Deep experience with Generative AI, LLMs, multi modal models, RAG systems, and agent-based architectures.· Strong knowledge of ML algorithms, NLP/NLU techniques, transformers, embeddings, and evaluation frameworks.Model Tuning & Optimization· Hands on expertise with PEFT, LoRA, QLoRA, parameter efficient fine tuning, and prompt tuning strategies.Frameworks, Tools & Libraries· Proficiency in:o LangChain, LangGraph, Pydantico FAISS / Chroma / Milvus or other vector DBso PyTorch / TensorFlowo HuggingFace ecosystemo OpenAI / Azure OpenAI / Claude / Gemini APIsFull Stack AI Engineering· Strong Python engineering skills for building orchestration, pipelines, and backend services.· Experience deploying AI workloads on Azure/AWS/GCP (or equivalents).· Understanding of MLOps / AIOps, CI/CD pipelines, containerization, and microservices.Consultative & Evangelization Skills - Exceptional communication and storytelling abilities.· Nice to have skills:8–15+ years of experience in AI/ML, with at least 3–5 years in GenAI/LLM-based solutions.· Master's degree or specialization in Computer Science, AI, ML, Data Science, or related fields.· Certifications in cloud AI services (Azure AI, AWS ML, GCP Vertex AI) are highly desirable.Key Responsibilities:1. Strategic AI Leadership & Evangelization - Partner with business and technology leaders to shape the AI roadmap, influence strategy, and embed AI in transformation initiatives.2. AI Solution Architecture & Full Stack AI Engineering - Lead design and development of end to end AI/GenAI solutions, including data ingestion, model orchestration, inference services, and integration with enterprise systems. Architect multi model pipelines using platforms and frameworks such as LangChain, LangGraph, Pydantic, vector databases, LLM frameworks, and cloud-native services.3. Model Development, Tuning & Optimization - Apply advanced model tuning techniques such as PEFT, LoRA, QLoRA, SFT, and Retrieval Augmented Generation (RAG).4. GenAI & ML Engineering Excellence - Build prototype agents, copilots, AI automation flows, and domain context solutions using modern AI frameworks.5. Client Engagement & Value Realization - Lead client discussions, articulate solution approaches, drive use case discovery, feasibility assessment, and ROI analysis to prioritize AI initiatives.Minimum years of experience:8-10 yearsCertifications Needed :NoTop 3 responsibilities you would expect the Subcon to shoulder and executeSolution designTechnical deliveryTeam handlingInterview Process (Is face to face required?)No