Zensar Technologies

AI Architect

Zensar Technologies
3.7/5 / 5
India Not disclosed
5 days ago
Remote
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About the job

Description Experience: 15+ years overall | Minimum 10 full-cycle AI/ML project implementations, including GenAI experience Role Summary: We are seeking a AI Architect to lead strategic AI transformation initiatives. 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 regulatory compliance. 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.

Requirements

  • AI
  • Machine Learning
  • Data Engineering
  • Cloud Architecture
  • Stakeholder Engagement

Preferred Technologies

  • AI
  • Machine Learning
  • Data Engineering
  • Cloud Architecture
  • Stakeholder Engagement

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