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.

AI Architect with Data Science -13+Years

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