Sr AI Platform Engineer - Retrieval & Knowledge Systems

Job Overview The Senior Engineer will design and build core AI knowledge infrastructure that powers intelligent applications across the enterprise. This role focuses on distributed systems, retrieval architectures, and AI platform services, enabling applications and agents to discover, retrieve, and reason over large‑scale enterprise data. Responsibilities AI Retrieval & Search Platform Design – Build high‑scale retrieval systems combining keyword search, semantic search, and vector‑based retrieval; develop RAG (Retrieval‑Augmented Generation) infrastructure including indexing, retrieval, ranking, and context assembly. Data Pipelines & Indexing Systems – Build streaming and batch pipelines for ingesting and transforming structured and unstructured data, including enrichment pipelines (chunking, embeddings, metadata extraction, classification); design real‑time indexing, incremental updates, and freshness guarantees; optimize data flow, storage, and compute efficiency at scale. AI Platform Services & APIs – Build low‑latency, highly available APIs that expose retrieval and knowledge services to applications and AI agents; develop reusable SDKs and service abstractions; enable context retrieval, query understanding, and response augmentation. LLM & Intelligent Systems Integration – Integrate LLMs with retrieval systems to enable grounded, context‑aware experiences; build systems for context construction, prompt augmentation, response orchestration; implement evaluation frameworks for relevance and grounding quality; support AI assistants, copilots, search experiences, and automation agents. Performance, Scalability & Reliability – Design for low‑latency ( Technical Leadership – Lead design and architecture of large‑scale AI platform components; mentor engineers; drive adoption of modern engineering practices (CI/CD, IaC, automated testing); partner with AI, data, and product teams to shape next‑gen intelligent platform capabilities. Qualifications Requirements: Minimum of 8 years of experience in backend or platform engineering. Experience building distributed systems, search platforms, or large‑scale data services. Hands‑on experience with APIs, microservices, and cloud‑native architectures. Experience with search systems, indexing, or retrieval pipelines. Proficiency in Java, Python, or Go. Preferences: Experience with cloud platforms and containerized environments (Kubernetes). Experience with Elasticsearch/OpenSearch, vector databases, or hybrid retrieval architectures. Familiarity with RAG systems, embeddings, and LLM integration patterns. Experience building AI platforms, copilots, or agent‑based systems. Experience with real‑time data systems (Kafka, streaming pipelines). Strong understanding of performance optimization in distributed systems. Pay Range $115,154.00 – $191,889.00 (actual base salary varies based on factors such as skill, experience, education, and geographic location). Benefits 401(k) matching Health benefits Employee stock options Paid time off Volunteer time off Other competitive total rewards package EEO. #J-18808-Ljbffr LPL Financial LLC