Overview
Senior Engineer in LPL's AI Engineering organization, architecting and leading production-grade agentic AI systems and generative model platforms, defining standards for safe deployment, governance and observability, and mentoring a growing team.
What you'll do
- Lead the end-to-end development of agentic AI systems leveraging AWS (SageMaker, Lambda, Step Functions, ECS/EKS) and open-source orchestration frameworks (LangChain, Hugging Face, etc.)
- Build reliable RAG and multi-agent architectures with vector databases (FAISS, Pinecone, OpenSearch)
- Drive model governance, including versioning, access control, audit trails, and risk reviews aligned with LPL's compliance standards
- Stay up-to-date on the latest advancements in industry and technology solutions, bringing insights to the team for continuous development of the stack, solutions and ways of working
- Partner with product and business stakeholders to identify and deliver high-impact AI opportunities across advisor experiences and enterprise automation
- Mentor engineers, set best practices, and guide the adoption of LLMOps and model observability
- Collaborate with cybersecurity, risk, and data governance teams to ensure responsible model usage and policy alignment
What you'll need
- Bachelor's or Master's degree in Computer Science, Data Science or a related field (years of experience may apply to cover this requirement)
- 7+ years of software engineering experience, with 3+ years leading ML/AI initiatives
- Strong experience building/managing agentic solutions, with solid understanding of agent orchestration, tool use, and guardrails for autonomous systems
- Strong experience building/managing Knowledge Graphs (entity extraction, linkage, ontology design)
- Experience integrating Knowledge Graphs with AI systems for retrieval, reasoning, and agent context (enriching with LLM)
- Proven expertise deploying ML and LLM solutions on AWS (SageMaker, Bedrock, ECS, Lambda)
- Deep knowledge of open-source ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
- Strong experience with MLOps and infrastructure-as-code (Terraform, Docker, Kubernetes)
Nice to have
- Familiarity with Azure AI, Vertex AI, or multi-cloud deployments
Details
Read the full description and apply on the company’s own careers page.