Product Manager - AI Strategy
EPAM Systems · Bengaluru, Karnataka, India
- On site
- Full-time
- $150,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Lead AI Model Ecosystem development in investment banking.
- Define product strategy and roadmap.
- Collaborate with engineering, data, and risk teams.
- Utilize SQL, Python, and AI coding agents.
- Manage end-to-end model lifecycle and risk.
About the role
About the Role
We are seeking an expert Product Manager to lead the development of a cutting-edge AI-driven Model Ecosystem within a dynamic investment banking environment. This pivotal role focuses on transforming the front-to-back model lifecycle by integrating advanced AI systems, data platforms and automation technologies. Collaborating across engineering, data and risk domains, you will play a crucial part in shaping innovative, scalable solutions for capital markets.
Responsibilities
- Define and own the product vision, strategy and roadmap for the AI-driven Model Ecosystem.
- Translate organizational objectives into clear product requirements, epics and user stories.
- Partner with engineering, data and risk teams to deliver end-to-end model lifecycle capabilities.
- Leverage SQL and Python for data analysis to drive informed product decisions.
- Architect and refine APIs, data models and system architecture requirements.
- Resolve complex high-impact product challenges with structured analysis.
- Act as a key liaison between business and technology teams to align goals and execution.
- Integrate Model Risk Management considerations into product workflows and design.
- Ensure robust testing and reliable delivery by collaborating with QA and engineering teams.
- Utilize AI coding agents and automation tools to streamline development cycles.
Requirements
- At least 10-15 years of experience in product analysis, technical product management or business analysis within financial services.
- Strong skills in SQL and Python for data analysis.
- Background in APIs, data models and system architecture.
- Deep understanding of product lifecycle management and agile delivery frameworks.
- Familiarity with Model Risk Management and model lifecycle processes.
- Expertise in cross-functional collaboration across engineering, data and business teams.
- Proficiency in stakeholder communication and management.
- Capability to utilize AI coding agents such as GitHub Copilot, Claude Code or AMP.
Nice to have
- Background in model lifecycle, validation or risk platforms.
- Experience with AI/ML platforms and agentic AI workflows.
- Understanding of data governance, lineage and regulatory requirements.
- Involvement in greenfield builds or large-scale transformation projects.
Key skills/competency
- Product Management
- AI Strategy
- Investment Banking
- Model Ecosystem
- Data Analysis (SQL, Python)
- APIs and Data Models
- System Architecture
- Model Risk Management
- Agile Delivery
- Stakeholder Communication
Skills & topics
- Product Manager
- AI Strategy
- Financial Services
- Investment Banking
- Model Ecosystem
- SQL
- Python
- APIs
- Data Models
- System Architecture
- Model Risk Management
- Agile
- EPAM Systems
How to get hired
- Tailor your resume: Highlight 10-15 years of product management experience in financial services, emphasizing AI, SQL, and Python skills.
- Showcase AI expertise: Detail your experience with AI coding agents like GitHub Copilot and knowledge of model risk management.
- Demonstrate collaboration: Provide examples of successful cross-functional work with engineering, data, and business teams.
- Prepare for technical questions: Be ready to discuss APIs, data models, system architecture, and your approach to complex product challenges.
- Understand the domain: Research EPAM Systems' work in AI and financial services transformation to align your answers with their objectives.
Technical preparation
Master SQL for data analysis and querying.,Strengthen Python skills for data manipulation.,Review API design and data modeling principles.,Understand AI coding agent functionalities.
Behavioral questions
Describe a complex product challenge you solved.,How do you translate business goals to requirements?,Share your experience managing cross-functional teams.,How do you integrate risk management into products?
Frequently asked questions
- What specific AI technologies are used in this Product Manager role at EPAM Systems?
- This Product Manager role focuses on an AI-driven Model Ecosystem, leveraging AI coding agents such as GitHub Copilot, Claude Code, or AMP. Experience with AI/ML platforms and agentic AI workflows is also beneficial.
- How important is financial services experience for the Product Manager - AI Strategy position?
- A strong background in financial services is critical, with at least 10-15 years of experience in product analysis, technical product management, or business analysis within this sector. Understanding Model Risk Management and the model lifecycle is also key.
- What data analysis tools will I use as a Product Manager at EPAM Systems?
- As a Product Manager, you will leverage SQL and Python for data analysis to drive informed product decisions. Familiarity with APIs, data models, and system architecture requirements is also expected.
- What does EPAM Systems look for in a candidate for the Product Manager - AI Strategy role?
- EPAM Systems seeks candidates with extensive experience (10-15 years) in financial services product management, strong technical skills in SQL and Python, expertise in AI technologies, and proven cross-functional collaboration abilities.
- Is this Product Manager role remote or on-site at EPAM Systems?
- The job description does not explicitly state the work arrangement. However, given the emphasis on collaboration and the dynamic environment of investment banking, it is likely a hybrid or on-site role.
- How can I best prepare for an interview for the Product Manager - AI Strategy position?
- Prepare by thoroughly reviewing your experience in AI, financial services, SQL, Python, and product lifecycle management. Be ready to discuss specific projects, your strategic approach, and how you handle complex technical and business challenges.