AI Architect with Data Science -13+Years

AI Architect/Lead-Data Science • Client is seeking a highly skilled AI Architect with a strong foundation in Data Science and deep expertise in Generative AI (GenAI) technologies. The ideal candidate will have hands-on experience designing, developing, and scaling AI/ML solutions, with a focus on LLMs, prompt engineering, and AI-driven applications. • This role requires a blend of strategic architecture, hands-on development, and leadership, enabling organizations to leverage cutting-edge AI capabilities for business transformation. • • Key Responsibilities • AI & GenAI Architecture • Design and implement scalable AI/ML and Generative AI architectures for enterprise use cases. • Lead the development of LLM-powered applications (chatbots, copilots, RAG systems, summarization engines). • Define architecture patterns for prompt engineering, fine-tuning, embeddings, and vector databases. • Evaluate and integrate GenAI tools, frameworks, and APIs. • • Data Science & Machine Learning • Apply strong data science expertise to design predictive and prescriptive models. • Build and optimize ML models using supervised/unsupervised learning techniques. • Guide teams on feature engineering, model evaluation, and deployment strategies. • Ensure alignment between traditional ML models and GenAI-based solutions. • • GenAI Tools & Technologies • Work extensively with: • LLMs (OpenAI, open-source models like LLaMA, Mistral) • Frameworks (LangChain, LlamaIndex, Haystack) • Vector databases (Pinecone, Weaviate, FAISS, Chroma) • Implement Retrieval-Augmented Generation (RAG) pipelines. • Design and optimize prompt strategies and guardrails. • • Cloud & MLOps • Architect AI solutions on cloud platforms (AWS, Azure, or GCP). • Implement MLOps pipelines for CI/CD, model monitoring, and lifecycle management. • Ensure scalability, performance, and cost optimization of AI workloads. • • Leadership & Strategy • Act as a technical leader and advisor for AI initiatives. • Collaborate with business stakeholders to identify AI opportunities. • Define AI governance, ethics, and responsible AI frameworks. • Mentor data scientists, ML engineers, and developers. • • Required Qualifications • Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field. • • 10+ years of IT experience with: • 5+ years in Data Science / Machine Learning • 3+ years in AI/ML Architecture • Strong hands-on experience in Python, SQL, and ML libraries (Scikit-learn, TensorFlow, PyTorch). • Proven experience with Generative AI and LLM-based solutions. • • Expertise in: • Prompt engineering • RAG architecture • Embeddings and semantic search • Experience with API integration and microservices architecture.