01Overview
A Bachelors or Higher Degree is the minimum entry required for the position
Role Overview
We are seeking a seasoned AI Architect to design and solution enterprise scale AI, Generative AI, Agentic AI, and LLM powered platforms for COE. The role focuses on scalable AI architecture, production deployment, governance, security, observability, and business value led solutioning across cloud and hybrid environments. Experience with Azure and AWS AI services is mandatory; exposure to SLM, domain SLM, ontology, and Knowledge Graphs is an added advantage.
Experience
Up to 18 years of overall IT experience
4+ years in AI/ML, Data Science, Advanced Analytics, GenAI, or Agentic AI
Proven experience in enterprise AI architecture, pre sales, RFPs, POCs, and production grade deployments
Exposure to AI use cases across BFSI, Manufacturing, Telecom, Healthcare, or similar domains
Key Responsibilities
Architecture & Solutioning
Define end to end AI, GenAI, and Agentic AI architectures for enterprise scale solutions.
Design LLM based systems including RAG, fine tuning, instruction tuning, multi agent orchestration, and autonomous workflows.
Translate business problems into scalable AI solutions across enterprise data platforms, Azure, AWS, and hybrid deployments.
Create reusable AI blueprints, accelerators, reference architectures, and governance models.
Engineering, Productionization & Governance
Architect robust data ingestion, feature engineering, model pipelines, and multimodal data integration.
Guide predictive, prescriptive, generative AI, NLP/NLU, semantic search, chatbot, and summarization solutions.
Implement MLOps/LLMOps, model lifecycle management, monitoring, observability, and continuous improvement.
Drive evaluation for accuracy, hallucination mitigation, bias, explainability, latency, cost, and scalability.
Embed Responsible AI, Zero Trust, data privacy, compliance, safety guardrails, and AI governance.
Stakeholder Engagement & Leadership
Lead client facing technical discussions, PoCs, demos, pre sales solutioning, and strategic AI advisory.
Collaborate with business stakeholders, product teams, and delivery teams to align AI solutions with outcomes.
Mentor data scientists, ML engineers, and AI developers on architecture, coding standards, and lifecycle best practices.
Evaluate emerging GenAI, Agentic AI, multimodal AI tools, platforms, frameworks, and accelerators.
Core Technology Stack
AI/ML/GenAI: ML, Deep Learning, NLP/NLU, Computer Vision, LLMs, RAG, embeddings, vector databases, prompt engineering, fine tuning
Frameworks: Python, Pandas, NumPy, Scikit learn, PyTorch, TensorFlow, LangChain, LangSmith, Langfuse, LlamaIndex, Semantic Kernel, FastAPI, Flask
Strong architectural mindset, problem solving ability, and enterprise solution design expertise
Excellent communication, stakeholder management, consulting, and client facing skills
Ability to connect AI architecture with measurable business value
Strong understanding of security, governance, Responsible AI, and scalable AI delivery
Qualifications
Background in Data Science, AI/ML, Computer Science, or related discipline
Azure and AWS AI certifications preferred .