• Act as a strategic AI/ML leader, identifying and executing use cases where AI can deliver automation, intelligent decision-making, predictive insights, and operational optimization.
• Manage medium to complex AI/ML and Gen AI projects from concept to deployment, demonstrating strong independent contribution across solution design, development, and delivery.
• Lead and coordinate cross-functional, geographically distributed teams (onshore, offshore, and outsourced) delivering critical AI applications and platforms enterprise-wide.
• Translate business requirements into functional specifications, ensuring seamless alignment with AI/ML models, data pipelines, and intelligent automation strategies.
• Conduct system and process analysis to identify opportunities for AI integration that enhance agility, customer experience, and internal efficiency.
• Perform impact assessments for AI-driven system enhancements, evaluating potential disruptions and opportunities through intelligent simulations and scenario modeling.
• Bridge the gap between domain experts and AI developers, translating complex business scenarios into structured data and model-ready formats.
• Independently prepare high-level scenarios and test data for Proof of Concept (POC) and internal testing of AI solutions without dependency on QA teams.
• Lead root cause analysis (RCA) using AI-based diagnostics, anomaly detection tools, and log intelligence to prevent recurrence of system disruptions.
• Maintain detailed documentation for AI system configurations, including model parameters, training datasets, pipeline dependencies, and operational workflows.
• Apply awareness of API architecture, data lineage, and system access to ensure AI models are securely and efficiently integrated across platforms.
• Use AI and ML tools to support debugging and resolution of complex issues, improving speed, accuracy, and reliability of technical troubleshooting.
• Drive service optimization and delivery excellence through the use of intelligent monitoring, automated workflows, and data-driven KPIs.
• Ensure AI/ML initiatives meet governance, audit, and regulatory compliance standards, with a focus on ethical AI, data privacy, and model explainability.
• Lead employee engagement and capability-building activities, with emphasis on AI fluency, experimentation, and adoption across teams.
• Oversee smooth transitions from development to production by embedding AI-based monitoring, alerting, and self-healing capabilities.
• Rigorously plan, execute, and finalize AI initiatives within deadlines, using intelligent project management and predictive planning tools.
• Coordinate with data engineering, infrastructure, and analytics teams to deliver seamless, scalable AI solutions that align with enterprise architecture.
• Maintain strict adherence to quality assurance and change management processes, exploring automation opportunities through AI-driven change risk assessments and documentation.
• Contribute to the full lifecycle of AI and Gen AI systems—including ideation, model design, prompt engineering, testing, deployment, and iterative refinement.
• Perform model selection, evaluation, and fine-tuning for Gen AI and Agentic AI use cases; build and orchestrate autonomous agents for dynamic workflows and decision support.
8 years of hands-on experience in AI/ML application development, with a focus on Generative AI and a research-oriented approach. Proven ability to apply theoretical knowledge to real-world challenges.
• Proficient in Python programming.
• Expertise in ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
• Expertise in both fundamental and advanced ML/GenAI techniques, including regression, classification, clustering, data synthesis, text/image processing, and more.
• Familiarity with message queues, Flask API/Fast API, storage and cloud technologies (Azure/AWS), Kubernetes/Docker, SQL, and testing frameworks.
• Having hands-on experience with Azure AI services, including Azure Machine Learning, Cognitive Services, and AI-based solutions for business applications, will be considered as an asset.
• Basic knowledge of Generative AI models, including Large Language Models (LLMs), Small Language Models (SLMs), and Retrieval-Augmented Generation (RAG), OpenAI. Familiarity with open-source models from Meta (Llama), Keras, Google, etc.
• Should have worked as part of functional consultant in Bank’s Product Designing with respect to Business requirements
• Strong understanding of SDLC and testing process
• Strong inter personal communication skills
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