Sr Director of Software Engineering (java, Aiml, Rag, Data/analytics)

JPMorgan Chase JPMorgan Chase · Banking · Hyderabad, Telangana, India · Consumer & Community Banking

Senior Director of Software Engineering at JPMorgan Chase to lead the development and evolution of a Product Tooling ecosystem. The role involves defining technical vision, driving architecture, and overseeing the delivery of mission-critical tooling that supports product management, planning, execution, and analytics. A key focus is championing the integration of AI technologies, including generative AI and RAG, to automate workflows, generate insights, and optimize product development processes. The role also includes leading engineering teams, ensuring platform scalability and security, and collaborating with stakeholders.

What you'd actually do

  1. Develop and execute the technology strategy for Product Tooling, aligning with organizational goals and the evolving needs of product teams.
  2. Lead the design and implementation of AI-powered features, including generative AI, Retrieval-Augmented Generation (RAG), and machine learning models to automate product management tasks, generate recommendations, and provide actionable insights.
  3. Oversee the development of tools that enhance product agility, such as backlog management, road mapping, prioritization, and cross-team collaboration platforms, while implementing consistent metrics and actionable insights to drive efficiency and effectiveness across product teams.
  4. Ensure the Product Tooling ecosystem is scalable, secure, and highly available, supporting thousands of users and integrating seamlessly with other enterprise systems. Oversee the design, development, of robust data pipelines to support analytics, AI, and product tooling features. Ensure data quality, integrity, and security across all product tooling systems.
  5. Build, mentor, and lead high-performing engineering teams, fostering a culture of innovation, technical excellence, and continuous improvement.

Skills

Required

  • 15+ years of professional experience in technology/software engineering leadership
  • proven track record of delivering large-scale, enterprise platforms
  • Bachelor’s or advanced degree in Computer Science, Engineering, or related field
  • Deep expertise in building product management tools, workflow automation platforms, or similar enterprise solutions
  • Demonstrated experience integrating AI technologies (such as generative AI, RAG, and ML) into product or workflow tooling
  • Strong experience with cloud technologies (AWS, Azure, or GCP), microservices, modern web frameworks and data engineering including designing and implementing scalable data architectures, and data integration solutions using cloud platforms
  • Experience leading multiple high-performing technology teams, managing managers, and mentoring principal engineers
  • Proven ability to deliver results in complex, fast-paced environments
  • Strong technical acumen, outcome-focused, and delivery-oriented
  • Experience engaging stakeholders to set strategy, align priorities, and deliver to a roadmap while adapting to changing business needs
  • Passion for building high-quality user experiences and a commitment to product excellence

Nice to have

  • Experience with AI-powered product management tools, automated documentation, and intelligent support systems
  • Hands-on experience with product agility frameworks (e.g., Scrum, Kanban, SAFe) and tools that support agile product development
  • Track record of delivering platforms in regulated environments
  • Experience with internal developer platforms and enterprise integrations

What the JD emphasized

  • 15+ years of professional experience in technology/software engineering leadership
  • proven track record of delivering large-scale, enterprise platforms
  • Demonstrated experience integrating AI technologies (such as generative AI, RAG, and ML) into product or workflow tooling
  • Experience leading multiple high-performing technology teams, managing managers, and mentoring principal engineers.

Other signals

  • integrating AI technologies
  • generative AI
  • RAG
  • machine learning models
  • automate product management tasks
  • generate recommendations
  • provide actionable insights
  • AI-driven solutions
  • data pipelines to support analytics, AI
  • AI-powered features