AVP, AI Accelerator Lead

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 We are seeking an AI Accelerator Lead to drive the design, delivery, and scaled adoption of AI/GenAI solutions across our Move Money, Banking, and Lending product lines on Web and Mobile . This is a hands-on leadership role blending AI strategy, solution architecture, and delivery execution—translating BFSI business problems into production-grade, compliant, and measurable AI capabilities. You will lead a cross-functional pod of AI/ML engineers, data scientists, and domain specialists, and act as the connective tissue between business, product, engineering, and risk/compliance.

Responsibilities

• Experience: 12+ years overall, with 5+ years in AI/ML and 4+ years in BFSI/fintech. Domain: Banking, Payments/Money Movement, Lendin. Platforms: Web & Mobile (iOS/Android). Type: Full-time, Leadership (Individual Contributor + People Leadership hybrid)
• AI Strategy & Accelerator Leadership: Define and own the AI roadmap for Move Money, Banking, and Lending, aligned to business OKRs and customer outcomes. Build and run an “AI accelerator” operating model—reusable frameworks, accelerators, patterns, and playbooks that speed up delivery across product teams. Identify, prioritize, and quantify high-ROI AI/GenAI use cases; drive build-vs-buy decisions.
• Solution Design & Delivery: Architect end-to-end AI/ML and GenAI solutions (data → model → deployment → monitoring) for web and mobile experiences. Lead delivery of use cases such as: fraud/risk detection, credit underwriting & decisioning, transaction categorization, payment anomaly detection, conversational banking assistants, document/KYC automation, and personalization. Ensure solutions are production-grade: scalable, observable, cost-optimized, and resilient.
• Domain Application (Move Money, Banking, Lending): Move Money/Payments: real-time fraud scoring, payment routing intelligence, AML/transaction monitoring, dispute automation. Banking: intelligent onboarding/KYC, personalized insights, virtual assistants, servicing automation. Lending: AI-driven credit risk models, alternative-data underwriting, income/document verification, collections optimization, explainable decisioning.
• Governance, Risk & Compliance: Embed responsible-AI and model-risk-management practices (bias, fairness, explainability, drift monitoring). Ensure compliance with BFSI regulations (e.g., fair lending/ECOA, KYC/AML, data privacy—GDPR/CCPA, model governance/SR 11-7 where applicable). Partner with Risk, Legal, and Compliance to establish guardrails for GenAI and data usage.
• Leadership & Enablement: Lead, mentor, and grow a multidisciplinary AI team (ML engineers, data scientists, MLOps). Upskill product and engineering teams on AI capabilities and adoption. Communicate strategy, trade-offs, and outcomes to senior/executive stakeholders.

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

• 12+ years of technology experience, including 5+ years in AI/ML and 4+ years in BFSI/fintech.
• Proven track record delivering production AI/ML systems at scale for web and mobile.
• Deep hands-on expertise in ML/DL and GenAI/LLMs (RAG, fine-tuning, prompt engineering, agentic workflows).
• Strong programming (Python) and ML frameworks (PyTorch/TensorFlow, scikit-learn); experience with LLM tooling (LangChain/LlamaIndex, vector DBs).. MLOps proficiency: model deployment, CI/CD for ML, monitoring, and lifecycle management on cloud (AWS/Azure/GCP).
• Solid grasp of data engineering (pipelines, feature stores…