AVP_ Data Products-Wealth Management and AI Data Products

GCC India
Hyderabad, Telangana

Apply Now

Job details

Full-time
9 hours ago

Qualifications

Law
Enterprise Software
Master's degree
Microservices
SQL
Distributed systems
Product management
APIs
AI
Communication skills
Python

Full job description

Where Ambition Meets Innovation

At LPL’s Global Capability Center, you'll find a collaborative culture where your voice matters, integrity guides every decision, and technology fuels progress. Your skills, talents, and ideas will redefine what's possible. LPL's success reflects its exceptional employees, who together pursue one noble purpose: empowering financial advisors to deliver personalized advice for all who need it. We’re proud to be expanding and reaching new heights in Hyderabad.

Join us as we create something extraordinary together.

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?

We’re 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.

LPL Global Business Services, LLP - PRIVACY POLICY

Apply Now

Jobseeker tools

Employer Tools

Browse

Stay Connected