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.