Software Engineer, AI Hub Platform
About the position Where Ambition Meets Innovation Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you’ll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals. As AI continues to transform how we build and deliver technology, LPL Financial is investing in shared, secure, and scalable AI platforms that empower product teams to innovate with confidence. This role offers the opportunity to work at the intersection of engineering, cloud, security, and AI—helping establish trusted foundations that accelerate AI-enabled solutions across the enterprise. Job Overview The AI Platform Analyst plays a critical role in building and evolving shared runtime services, control plane capabilities, and core platform components that enable teams to develop and operate AI-enabled applications safely in production. This role focuses on platform capabilities that must be consistent across teams, including model access, policy enforcement, tenant isolation, observability, auditability, and tool integration. Working closely with architecture, security, cloud, and product partners, this role helps define and deliver “paved paths” that reduce friction, lower risk, and speed time to production for AI solutions across LPL. Responsibilities • Design and build core AI Hub platform services, APIs, SDKs, and runtime components • Implement shared platform controls including authentication, authorization, policy enforcement, rate limiting, audit logging, and tenant isolation • Develop integration patterns for model providers, retrieval systems, tool registries, and orchestration frameworks • Build production-grade services for AI request routing, session and context handling, tool invocation, and response assurance • Partner with architecture, security, cloud, and product teams to define standardized approaches for AI delivery • Improve platform reliability, scalability, cost efficiency, and operational transparency • Contribute to engineering standards for testing, deployment, telemetry, and secure software development for AI workloads Requirements • 7-12 years of software engineering experience with distributed systems, APIs, and cloud-native platforms • 7-12 years experience building or supporting shared platforms or internal developer platforms • 7-12 years experience using Java, Python, or similar backend programming languages • 5+ years experience with cloud services, containers, event-driven architectures, and service integration patterns • 2-3 years of experience with AI/LLM system building blocks such as model gateways, vector retrieval, tool calling, or agent orchestration • Platform thinking and systems design • Operational excellence and reliability engineering • Secure-by-design development practices • Analytical problem-solving • Cross-team collaboration Nice-to-haves • A strong technical foundation with a passion for building shared platforms that scale across teams • The ability to translate ambiguous platform needs into clear, implementable solutions • A collaborative mindset and comfort working across architecture, security, and product stakeholders • Curiosity and continuous improvement in emerging AI and platform technologies Benefits • 401K matching • health benefits • employee stock options • paid time off • volunteer time off