Senior AI Platform Engineer, Retrieval & Knowledge Systems

LPL Financial

Quick summary

Work type
On-site
Location
SC
Salary
$115,154–$191,889 / yr
Posted
2 days ago
Nearby
9 roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k
This role $154k
$98k most similar roles pay here $275k

This role pays less than 82% of similar roles. Most pay $167,449–$240,387 — the shaded band above. At the midpoint, this role pays about $154k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About LPL Financial

LPL Financial is the largest independent broker-dealer in the United States, providing brokerage and investment advisory services to independent financial advisors and financial institutions. Industry: Financial Services & Wealth Management

LPL Financial currently has 45 open roles on FindRole.

Listed pay typically runs $135,960–$226,600 across 45 roles with salary data.

Most-posted roles

View all roles at LPL Financial

At a glance

TL;DR · Senior AI Platform Engineer, Retrieval & Knowledge Systems

Role Posting Log in to save

The Senior Engineer role involves designing and building core AI knowledge infrastructure for enterprise-wide intelligent applications, focusing on distributed systems, retrieval architectures, and AI platform services. Day-to-day responsibilities include developing high-scale retrieval systems, RAG infrastructure, data pipelines, indexing systems, and low-latency APIs that expose retrieval and knowledge services to downstream teams. The ideal candidate has extensive experience in backend or platform engineering, with a focus on distributed systems, search platforms, and cloud-native architectures. Proficiency in Java, Python, or Go is essential, along with familiarity with Elasticsearch/OpenSearch, vector databases, and real-time data systems like Kafka. This role requires expertise in performance optimization and technical leadership to drive the development of next-generation intelligent platform capabilities at a large scale.

Skills

Python Java Go Kubernetes Elasticsearch OpenSearch Docker CI/CD Terraform AWS PostgreSQL Redis Prometheus Grafana Kafka LLMs RAG Vector_Databases Microservices Cloud_Native_Architectures

What you'll do

  • Design and build high-scale retrieval systems combining keyword search, semantic search, and vector-based retrieval.
  • Develop RAG infrastructure including indexing, retrieval, ranking, and context assembly.
  • Build and optimize search indices, vector stores, and hybrid retrieval systems for relevance, latency, and scale.
  • Implement advanced ranking, relevance tuning, and personalization pipelines.
  • Establish patterns for multi-tenant, scalable platform services and build low-latency APIs exposing retrieval and knowledge services.

What we're looking for

  • Minimum 8 years of backend or platform engineering experience.
  • Expertise in distributed systems, search platforms, and large-scale data services.
  • Hands-on experience with APIs, microservices, and cloud-native architectures.
  • Proficiency in Java, Python, or Go programming languages.
  • Experience with Elasticsearch/OpenSearch, vector databases, and hybrid retrieval.
  • Familiarity with RAG systems, embeddings, LLM integration patterns.

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