Senior Manager - IBG & Ops.MGN Pak - TECH - IBG & Automation.MIT

• Lead the design, development, and implementation of AI/ML, Generative AI (Gen AI), and Agentic AI solutions aligned with business transformation objectives.
• Collaborate with business stakeholders and technology teams to identify AI-driven opportunities that enhance operational efficiency, customer experience, and decision-making capabilities.
• Responsible for end-to-end delivery of AI initiatives, including problem framing, data exploration, model development, validation, deployment, and post-production monitoring.
• Drive innovation by conducting POCs and developing scalable prototypes using Gen AI and Agentic AI frameworks.
• Provide functional and technical leadership across AI domains—ensuring models are explainable, ethical, and in line with regulatory and governance requirements.
• Work cross-functionally to integrate AI capabilities into existing platforms and workflows, while promoting the adoption of emerging technologies such as autonomous agents and intelligent decision systems.
• Act as a subject matter expert for AI-related tools, platforms, and best practices, offering guidance and training to business and technical teams.

•    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