DE&A - AIML - Data Science - Data Science (Other)
India
Zensar
Zensar is a global organization which conceptualizes, builds, and manages digital products through experience design, data engineering, and advanced analytics for over 200 leading companies. Our solutions leverage industry-leading platforms to...Experience: 15+ years overall | Minimum 10 full-cycle AI/ML project implementations, including GenAI experience
Location: Pune/ Hyderabad/ Bangalore (With Atleast one Architect from Hyderabad)
Role Summary:
We are seeking a AI Architect to lead strategic AI transformation initiatives within the Banking, Financial Services, and Insurance (BFSI) domain. This role demands deep hands-on experience in AI, Machine Learning (ML), and Generative AI (GenAI), along with the ability to engage directly with C-level stakeholders, align technical delivery with business objectives, and drive enterprise-wide adoption of advanced AI solutions.
The ideal candidate is a techno-strategic leader who can take AI/ML/GenAI projects from ideation to production—building architectures, leading cross-functional teams, and ensuring regulatory and operational alignment in BFSI environments.
Key Responsibilities:
Consulting & Business Alignment
• Partner with senior business and IT leadership, including CIOs, CDOs, and COOs, to identify high-impact use cases across retail banking, insurance, credit, and capital markets.
• Translate complex BFSI challenges into technically feasible and scalable AI/ML/GenAI solutions.
• Create strategic roadmaps, capability assessments, and PoV/PoC execution plans that align with business KPIs and regulatory needs.
Solution Architecture & Delivery Leadership
• Design and lead delivery of AI/ML/GenAI pipelines covering data ingestion, model training, validation, deployment, and monitoring.
• Build and scale GenAI-based solutions like LLM-driven chatbots, intelligent document processing, RAG pipelines, summarization tools, and virtual assistants.
• Architect cloud-native AI platforms using AWS (SageMaker, Bedrock), Azure (ML, OpenAI), or GCP (Vertex AI, BigQuery, LangChain).
• Define and implement MLOps and LLMOps frameworks for versioning, retraining, CI/CD, and production observability.
• Ensure adherence to Responsible AI principles, including explainability, bias mitigation, auditability, and compliance with BFSI regulations (GDPR, RBI, SOC2, etc.).
Engineering & Integration
• Work closely with data engineering teams to acquire, transform, and pipeline data from core banking systems, CRMs, claims systems, and real-time feeds.
• Design architecture for data lakes, feature stores, and vector databases supporting AI and GenAI use cases.
• Enable seamless integration of AI capabilities into enterprise workflows, customer platforms, and decision engines via APIs and microservices.
Required Skills & Experience:
• 15+ years of experience in AI/ML, data engineering, and cloud architecture.
• Minimum of 10 end-to-end AI/ML project implementations from use case discovery through to productionization.
• Proven expertise in: (Any One)
• AI/ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch
• GenAI/LLM platforms: OpenAI, Cohere, Mistral, LangChain, Hugging Face, vector DBs (Pinecone, FAISS, Chroma)
• Cloud platforms: AWS, Azure, GCP – including AI/ML & GenAI native services
• MLOps/LLMOps tools: MLflow, Kubeflow, SageMaker Pipelines, Vertex AI Pipelines
• Strong experience with data security, governance, model risk management, and AI compliance frameworks relevant to BFSI.
• Ability to lead large cross-functional teams and engage both technical teams and senior stakeholders.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Architecture AWS Azure Banking BigQuery Chatbots CI/CD CoHere Consulting Engineering FAISS GCP Generative AI KPIs Kubeflow LangChain LLMOps LLMs Machine Learning Microservices MLFlow MLOps Model training OpenAI Pinecone Pipelines PyTorch RAG Responsible AI SageMaker Scikit-learn Security TensorFlow Vertex AI XGBoost
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