CodeVyasa
Website:
codevyasa.com
Job details:
Job Description
We are seeking a highly dynamic, hybrid Technical Project Manager (TPM) and Data Product Manager ll 8+ yrs of exp. ll Bengaluru to drive a large-scale AI Strategy Implementation within the Life Insurance and Financial Services sector. In this critical role, you will define the vision, roadmap, and requirements for enterprise AI capabilities, and will own the foundational data products used by business teams for AI and reporting use cases. You will also orchestrate the engineering execution, release planning, and cross-functional coordination.
About the Company
CodeVyasa is a mid-sized product engineering company that works with top-tier product and solutions organizations such as McKinsey, Walmart, RazorPay, Swiggy, and others. We are a team of 550+ engineers, driving innovation across Product & Data Engineering, focusing on Agentic AI, RPA, Full Stack, and GenAI-based solutions.
Responsibilities
- Data Product Ownership: Own the full lifecycle of specific reusable data products and foundational AI components, including their definition, development, adoption, and ongoing maintenance/deprecation.
- Requirement Gathering & Discovery: Lead client-facing workshops and discovery sessions to gather, define, and document complex business and technical requirements for AI use cases and reusable data products.
- Roadmap Development: Build, own, and maintain the strategic product roadmap for the Data & AI Platform, ensuring alignment with the broader enterprise AI strategy and LBU-specific needs.
- Product Vision: Translate high-level business objectives (e.g., automating underwriting, intelligent document processing) into actionable product features, user stories, and technical specifications.
- Release Planning & Delivery: Drive end-to-end release planning, sprint management, and delivery schedules. Ensure timely rollout of AI platform capabilities across multiple global markets (LBUs).
- Data Governance & Modeling: Lead data mapping and modeling exercises, ensuring all data consumed by or produced by the AI Platform aligns with the enterprise data model, governance standards, and lineage documentation.
- Engineering Coordination: Partner closely with Machine Learning Architects, GenAI Engineers, and Data Engineering teams to guide the technical implementation of the AI strategy.
- Cross-Team Orchestration: Act as the central point of coordination between the "Platform Implementation Team" and external "Use Case Implementation Partners," ensuring seamless integration and dependency management.
- Executive Reporting: Design and deliver clear, high-impact executive reports, dashboards, and presentations detailing project health, roadmap progress, risks, and ROI.
- Stakeholder Alignment: Manage expectations across a complex matrix of stakeholders, including Group-level executives, LBU data teams, and third-party consulting partners.
- Risk & Issue Management: Proactively identify bottlenecks, technical blockers, and scope creep, implementing effective mitigation strategies to keep the AI implementation on track.
- Stakeholder Requirement Management: Proactively engage with business stakeholders (LBU leadership, business analysts) to capture, prioritize, and manage ongoing requirements, feature requests, and changes to deployed AI products and platform capabilities.
- Internal Product Collaboration: Establish a strong partnership with other Product Managers, Data Modellers, and Data/ML Engineers across the organization to ensure technical alignment, shared component reuse, and seamless data flow across the enterprise data ecosystem.
Qualifications
- 8+ years of hybrid experience in Technical Project Management and Product Management, specifically within Data, Analytics, or AI/ML software development.
Required Skills
- Client-Facing & Consulting Expertise: Proven track record in a client-facing capacity, with extensive experience leading technical discovery workshops, shaping solution architectures, and driving proposal/RFP development.
- AI/ML Lifecycle Acumen: Strong conceptual understanding of Machine Learning lifecycles, Generative AI (LLMs, RAG), MLOps, and multi-cloud data architectures (Azure/GCP). Note: Coding is not required, but technical fluency is mandatory.
- Agile Mastery: Deep expertise in Agile/Scrum methodologies, backlog grooming, capacity planning, and utilizing tools like Jira, Confluence, and MS Project.
- Release Management: Proven ability to manage complex, multi-phase release cycles in an enterprise environment.
- Exceptional verbal and written communication skills, with the ability to translate complex technical AI concepts into clear business value for non-technical executives.
- Strong negotiation and conflict-resolution skills to manage competing priorities across different regional business units.
- Highly organized, detail-oriented, and capable of thriving in an ambiguous, fast-paced enterprise transformation environment.
Preferred Skills
- Certifications such as PMP, PMI-ACP, Certified ScrumMaster (CSM).
- Prior experience managing the rollout of enterprise-wide "Platform-as-a-Service" (PaaS) or reusable API business services.
- Industry Knowledge: Familiarity with Life Insurance and Financial Services business processes (e.g., Customer & Household, Distribution, Underwriting, Claims Servicing).
- Regulatory Awareness: Understanding of data governance, compliance, and risk management principles inherent to the BFSI sector.
- Bachelor’s or Master’s Degree in Computer Science, Information Systems, Business Administration, or a related field.
Why Join CodeVyasa?
- Work on innovative, high-impact projects with leading global clients.
- Exposure to modern technologies, scalable systems, and cloud-native architectures.
- Continuous learning and upskilling opportunities through internal and external programs.
- Supportive and collaborative work culture with flexible policies.
- Competitive salary and comprehensive benefits package.
- Free healthcare coverage for employees and dependents.
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