Job Title

Job Description: Principal AI/ML Architect – GenAI & Agentic AIRole OverviewWe are looking for a Principal AI/ML Architect with deep expertise in Traditional Machine Learning, Generative AI, and Agentic AI architectures to lead the design and delivery of enterprise-scale AI solutions. This role requires strong hands-on capability along with architectural ownership, stakeholder engagement, and technical leadership across the AI lifecycle.Experience14 to 24 years of overall IT experience10+ years of hands-on experience in Data Science / AI / MLPrior experience in Architect / Principal / Lead roles is mandatoryKey ResponsibilitiesArchitect, design, and lead end-to-end AI/ML and GenAI solutions from ideation to productionDefine enterprise-grade architectures for:Traditional ML & Deep Learning systemsGenerative AI (LLMs) use casesRAG, Self-RAG, and advanced retrieval pipelinesAgentic AI / Multi-Agent orchestration frameworksOwn solution design covering:Data ingestion, feature engineering, model trainingDeployment, monitoring, retraining, and drift detectionDesign scalable AI services using microservices and event-driven architecturesLead MLOps pipelines for CI/CD, model versioning, monitoring, and governanceWork closely with business stakeholders to translate requirements into AI-driven solutionsMentor and guide teams of data scientists, ML engineers, and MLOps engineersDrive POCs, innovation initiatives, and adoption of state-of-the-art AI techniquesEnsure solutions meet performance, security, compliance, and explainability standardsTechnical Skills – MandatoryAI / ML / GenAIMachine Learning, Deep Learning, NLP, Computer VisionGenerative AI using GPT, LLaMA, Mistral, Claude or equivalent LLMsRAG, Self-RAG, embeddings, vector databasesAgentic AI / Multi-Agent frameworks (LangChain, LangGraph, AutoGen, CrewAI or similar)Statistical modeling, feature engineering, model evaluationProgramming & FrameworksPython (strong hands-on)TensorFlow / PyTorch / KerasREST APIs & microservicesCloud & MLOpsAWS / GCP / Azure (any one mandatory, multi-cloud preferred)Docker, KubernetesCI/CD pipelines, model monitoring, logging, drift detectionTools like SageMaker, Bedrock, Airflow, MLflow (or equivalents)Data & PlatformsSQL & NoSQL databasesVector databases & knowledge graphsKafka / SQS or similar event-driven systemsNice to HaveExperience in Banking, Financial Services, Investment Banking, Healthcare, or AutomationExperience handling large-scale enterprise AI deploymentsExposure to Explainable AI, Responsible AI, AI governanceStrong understanding of Agile delivery modelsSoft SkillsStrong communication and stakeholder managementAbility to translate business problems into AI solutionsTechnical leadership and mentoring capabilityStrategic thinking with hands-on execution mindsetRole LevelPrincipal / Architect / Senior Architect – AI & GenAIIndividual contributor with technical ownership and leadership responsibilities