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LPL Financial LLC’s Global Capability Center in Hyderabad seeks an AVP of Engineering to lead a team modernizing the advisor experience portfolio. You will drive cloud-native delivery, institute strong engineering discipline, and introduce practical AI capabilities to improve speed, accuracy, and governance.
You will mentor engineers, shape architecture, and partner with Product, Security, and Operations to deliver high-impact capabilities while managing risk and ensuring production stability.
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 expanding and reaching new heights in Hyderabad. Join us as we create something extraordinary together. AVP, Software Engineering — Practice Management | LPL Technologies At LPL Financial 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 are proud to expand in Hyderabad. Join us as we create something extraordinary together.
Practice Management is where the firm’s operating rhythm meets the advisor experience: onboarding advisors and practices, managing compensation, registrations, fees, and the workflows operations teams run every day. We are hiring an AVP of Engineering to lead a talented team modernizing this portfolio—raising quality, increasing velocity safely, and shipping capabilities that advisors and internal partners feel immediately. If you want a high-trust leadership seat with real technical depth—cloud-native delivery, strong engineering discipline, and practical AI (not hype)—this is a standout opportunity at LPL.
You are expected to be technically credible with complex enterprise systems—even as your primary job is leading the team. You should be comfortable diving into architecture reviews, critical incidents, and the hardest design decisions.
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.
12+ years software engineering experience in enterprise environments; 5+ years leading engineering teams (managers and senior ICs). Track record shipping and operating mission-critical applications; experience in regulated / financial services strongly preferred. Strong Oracle PL/SQL engineering: packages, procedures, functions, triggers, bulk operations, and complex business logic in production. Strong SQL tuning and performance work: execution plans, indexing, AWR/ASH, partition strategy, production query optimization, process troubleshooting, and data flow analysis. Strong relational data modelling and operational data discipline; Demonstrated success leading modernization programs (incremental migration, platform patterns, service boundaries, strangler approaches) while keeping production stable. Ability to introduce AI-enabled capabilities and/or AI-accelerated engineering with measurable impact and appropriate controls.
Domain familiarity with advisor/practice onboarding, compensation, registration/licensing workflows, or fee/billing platforms. Experience with distributed systems, APIs, event-driven patterns, and pragmatic microservices where they earn their complexity. Background shaping CI/CD, automated testing strategy, SRE practices, incident learning, and engineering metrics. Familiarity with model/workflow governance, monitoring, and responsible AI practices in enterprise settings. Experience with .NET / C# and cloud-native engineering on AWS (compute, data, messaging/integration, identity patterns, observability). Comfort with Python for automation, services, or data/AI-adjacent workloads.
Systems thinking, decisive prioritization, calm under ambiguity, and executive-ready communication. You raise the bar by clarifying standards, not by adding process for its own sake.