Sr AI Platform Engineer – Retrieval & Knowledge Systems

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.

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. You will work at the intersection of search, vector retrieval, LLMs, and real-time data systems, building high-performance platforms used by AI and application teams.

The ideal candidate is a strong backend/platform engineer with deep experience in building scalable systems and modern AI-powered retrieval architectures.

Responsibilities:

AI Retrieval & Search Platform

• Design and buildhigh-scale retrieval systems combining keyword search, semantic search, and vector-based retrieval.

• DevelopRAG (Retrieval-Augmented Generation) infrastructure including indexing, retrieval, ranking, and context assembly.

• Build and optimizesearch indices, vector stores, and hybrid retrieval systems for relevance, latency, and scale.

• Implementadvanced ranking, relevance tuning, and personalization pipelines.

Data Pipelines & Indexing Systems

• Buildstreaming and batch pipelines for ingesting and transforming structured and unstructured data.

• Developenrichment pipelines (chunking, embeddings, metadata extraction, classification).

• Design systems forreal-time indexing, incremental updates, and freshness guarantees.

• Optimizedata flow, storage, and compute efficiency at scale.

AI Platform Services & APIs

• Buildlow-latency, highly available APIs that expose retrieval and knowledge services to applications and AI agents.

• Develop reusableSDKs and service abstractions for easy integration into product teams.

• Enablecontext retrieval, query understanding, and response augmentation for downstream AI systems.

• Establish patterns formulti-tenant, scalable platform services.

LLM & Intelligent Systems Integration

• IntegrateLLMs with retrieval systems to enable grounded, context-aware experiences.

• Build systems forcontext construction, prompt augmentation, and response orchestration.

• Implementevaluation frameworks for relevance, grounding quality, and user experience.

• Support use cases likeAI assistants, copilots, search experiences, and automation agents.

Performance, Scalability & Reliability

• Design forlow-latency (<100ms retrieval), high-throughput, and horizontal scalability.

• Implementcaching, sharding, and distributed query execution strategies.

• Buildobservability pipelines (metrics, logs, tracing) for system performance and usage insights.

• Driveresiliency, fault tolerance, and system reliability at scale.

Technical Leadership

• Lead design and architecture oflarge-scale AI platform components.

• Mentor engineers ondistributed systems, retrieval architectures, and AI engineering practices.

• Drive adoption ofmodern engineering practices (CI/CD, infrastructure-as-code, automated testing).

• Partner with AI, data, and product teams to shapenext-gen intelligent platform capabilities.

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 candidatespursue greatness,act with integrity, and aredriven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where wewin together andcreate and share joy in our work.

Requirements:

• Minimum of 8 years of experience inbackend or platform engineering.

• Experience buildingdistributed systems, search platforms, or large-scale data services.

• Hands-on experience withAPIs, microservices, and cloud-native architectures.

• Experience withsearch systems, indexing, or retrieval pipelines.

• Experience programming skills inJava, Python, or Go.

Preferences:

• Experience withcloud platforms and containerized environments (Kubernetes).

• Experience withElasticsearch/OpenSearch, vector databases, or hybrid retrieval architectures.

• Familiarity withRAG systems, embeddings, and LLM integration patterns.

• Experience buildingAI platforms, copilots, or agent-based systems.

• Experience withreal-time data systems (Kafka, streaming pipelines).

• Strong understanding ofperformance optimization in distributed systems.

 

Pay Range:

$115,154.00 - $191,889.00

 

Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play – such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!

 

Company Overview:

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace(6) , LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans. The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses. For further information about LPL, please visit www.lpl.com.

At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.

For further information about LPL, please visitwww.lpl.com.

Join the LPL team and help us make a difference by turning life’s aspirations into financial realities. Please log in or create an account to apply to this position. Principals only. EOE.

Information on Interviews:

LPL will only communicate with a job applicant directly from an @lplfinancial.com email address and will never conduct an interview online or in a chatroom forum.  During an interview, LPL will not request any form of payment from the applicant, or information regarding an applicant’s bank or credit card.  Should you have any questions regarding the application process, please contact LPL’s Human Resources Solutions Center at (855) 575-6947.

EAC 5.19.26