Principal Solution Architect - AI

What if you could build a career where ambition meets innovation? At LPL Financial, we empower professionals to shape their success while helping clients pursue their financial goals with confidence. What if you could have access to cutting-edge resources, a collaborative environment, and the freedom to make an impact? If you're ready to take the next step, discover what’s possible with LPL Financial.

The AI Solution Architect is a senior technical leader responsible for designing, architecting, and operationalizing Agentic AI and Generative AI solutions across the enterprise. This role is central to shaping and implementing an AI‑first Product Delivery Lifecycle (PDLC)—ensuring that LPL’s product development processes, engineering practices, and operating models are optimized for AI‑native platforms, agentic systems, and rapid-value iteration.

• AI Architecture & Solution Design

• Architect enterprise-scale Agentic and Generative AI systems, including orchestration frameworks, multi-agent workflows, retrieval-augmented generation (RAG), and autonomous task execution patterns.

• Establish reference architectures for AI-first PDLC covering design, development, testing, deployment, monitoring, and risk controls.

• Partner with product and engineering teams to embed AI capabilities into advisor- and client-facing systems, internal tooling, and operational workflows.

• Lead the architectural design of model lifecycle pipelines, including training, fine-tuning, evaluation, and model governance.

• PDLC Transformation

• Define the architecture, tools, and methods required for an AI-native delivery lifecycle—integrating prompting, agent design, model testing, AI risk/controls, and continuous learning loops.

• Develop standards to upskill teams into AI “builders” across product, engineering, design, and risk disciplines.

• Influence enterprise-wide adoption of AI-driven development patterns, including automated evaluation harnesses, safety guardrails, and data quality validation.

• Enterprise Integration & Data Strategy

• Design integrations between AI systems, core platforms (Client Works, Account Lifecycle), and enterprise data ecosystems.

• Partner with Data Engineering to define data ingestion, vectorization, feature storage, and real-time inference pipelines.

• Ensure architectural alignment with cloud strategy, data governance, and enterprise controls.

• Security, Compliance & Responsible AI

• Ensure all AI solutions meet LPL’s regulatory and compliance obligations.

• Collaborate with Info Sec to embed identity, authorization, auditing, and model‑level security patterns.

• Implement Responsible AI guidelines covering transparency, fairness, evaluation, and model performance monitoring.

• Cross-Functional Leadership

• Partner with senior leaders across Product, Enterprise Architecture, Dev Sec Ops , Operations, and Infrastructure to drive alignment and prioritization.

• Lead architectural reviews, whiteboarding sessions, and candidate architecture evaluations.

• Mentor engineering teams and contribute to LPL’s AI architecture community of practice.

• Support hiring and talent strategy for emerging AI roles.

What are we looking for? We want strong collaborators who can deliver a world-class client experience
. We are looking for people who thrive in a fast-paced environment, are client-focused, team oriented
, and are able to execute in a way that encourages creativity and continuous improvement
.

• 2+ years experience architecting Generative AI, Agentic AI, and ML systems at enterprise scale.

• 6+ years experience with cloud-native architecture background (AWS preferred), including microservices, Kubernetes, and event-driven patterns.

• 5+ years experience with LLMs, vector databases, embeddings, evaluators, guardrails, fine-tuning, and orchestration.

• 8+ years experience in Python; proficiency in C#, Java, or Type Script is a plus.

• 6+ years expertise with ML Ops including CI/CD for ML, model versioning, monitoring, automated evaluation.

• Bachelor’s degree in Computer Science, Engineering, AI/ML, or equivalent experience.

• AWS Solutions Architect – Professional, AWS Machine Learning Specialty, Terraform Associate, or similar…