Data Products-Wealth Management Automation and Data Products

LPL Financial Global Capability Center; Hyderabad; Hybrid; INR 2,800,000 - 6,000,000; Full time

Job summary

LPL Financial seeks an AVP, Data Product Owner (DPO) to guide Wealth Management data products and drive AI-powered workflow automation across the enterprise data ecosystem.

The role blends strategic leadership with hands-on oversight of AI agent frameworks, ensuring production-ready deployments aligned with governance, security, and business outcomes.

Qualifications

• 7-10+ years in data products or product management roles.
• Strong SQL and data platform experience (data lakes, pipelines).
• Proficiency in Python with AI/ML workflow exposure.
• Experience designing AI agents or automation systems in enterprise env.
• Proven cross-functional leadership across engineering and business teams.

Responsibilities

• Define AI-driven workflow automation strategy for the data ecosystem.
• Lead design and deployment of AI agents and reusable automation frameworks.
• Set standards for agent orchestration, tool integration, and system design.
• Oversee data models, pipelines, lineage, and governance tooling.
• Collaborate with governance, security, and business teams to ensure outcomes.

Skills

SQL

Python

AI workflows

Leadership

Tools

APIs

LangChain

Bedrock

Data pipelines

Job description

Job Overview:

LPL Financial is seeking an AVP, Data Product Owner (DPO) to lead Wealth Management (WM) data products while driving large-scale adoption of AI-powered workflow automation across the enterprise data ecosystem.

This role combines strategic Data Product Leadership with hands-on oversight of AI agent frameworks and automation platforms. The AVP will define the roadmap for AI-enabled data products, guide teams in building scalable agent-based systems, and ensure production-ready deployment aligned with governance, security, and business outcomes.

Responsibilities

AI Strategy and Innovation

• Define and lead the strategy for AI-driven workflow automation across the data ecosystem.
• Oversee the design and implementation of AI agents and reusable automation frameworks.
• Establish best practices for agent orchestration, tool integration (APIs, SQL, metadata platforms), and system design.
• Define evaluation, monitoring, and reliability standards for AI systems (guardrails, observability, performance tracking).
• Drive reuse and scalability of AI capabilities across multiple data domains.

Technical & Cross-Functional Leadership

• Partner with Engineering, Architecture, and Business teams to deliver AI-enabled solutions.
• Translate strategic business needs into scalable AI and data product architectures.
• Provide oversight on data models, pipelines, lineage, and integrations.
• Influence platform decisions related to AI, data catalog, and governance tools.

What are we looking for?

Were looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

Requirements:

• 7 - 10+ years of experience in Data Products, Product Management, Applied AI, or platform-oriented roles.
• Strong expertise in SQL and data platforms (distributed systems, data lakes, integration layers).
• Strong Python proficiency with experience in AI/ML workflows and automation systems.
• Experience designing and scaling AI agents or workflow automation systems in enterprise environments.
• Experience defining AI architecture patterns involving tool-using agents (APIs, SQL, enterprise systems).
• Experience working with LLM platforms (Amazon Bedrock preferred or equivalent).
• Strong understanding of production-grade AI systems, including monitoring, observability, and reliability patterns.
• Proven ability to lead cross-functional teams and deliver complex data and AI initiatives.

Core Competencies:

• Strong leadership and strategic thinking.
• Deep understanding of data governance, quality, and lineage.
• Ability to translate AI innovations into scalable enterprise solutions.
• Strong communication and stakeholder management across executive and technical audiences.
• Experience operating in regulated environments (financial services preferred).
• Focus on scalability, reliability, and trust in AI-enabled systems.

Preferences:

• Experience with agent frameworks (LangGraph, LangChain Agents, or similar).
• Familiarity with context management techniques such as embeddings, vector databases, or Retrieval-Augmented Generation (RAG).
• Experience with event-driven or microservices-based architectures.
• Exposure to model evaluation techniques and AI performance benchmarking.