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LPL Financial

AVP, AI Solutions Engineer

LPL Financial

AI Solutions Engineer designing and implementing AI solutions for data governance at LPL Financial. Requires strong AI/ML integration skills and experience with AWS and modern orchestration frameworks.

Posted 5/22/2026full-timeNew York City • New York, Texas • 🇺🇸 United StatesLead💰 $146,900 - $244,900 per yearWebsite

Tech Stack

Tools & technologies
AngularAWSCloudMicroservices.NETPythonRayRPASDLC

About the role

Key responsibilities & impact
  • Embed AI-first and ML engineering principles into SDLC, ensuring intelligent automation and predictive capabilities are considered from design through deployment.
  • Design and develop agentic AI solutions for: Data governance tracking and compliance monitoring.
  • Exception detection and resolution across multiple data domains.
  • Reconciliation frameworks using rule-based and AI-driven logic.
  • Lifecycle management workflows for investor and operational domains.
  • Build intelligent agents that apply rules or adaptive intelligence to automate exception handling and reconciliation.
  • Develop APIs and microservices using Python (FastAPI) and .NET Core for agentic workflows.
  • Integrate AI workflows with LDX UI components built in Angular for user review and configuration.
  • Implement event-driven architectures using AWS EventBridge, Lambda, and Step Functions for real-time orchestration.
  • Deploy and manage LLMs (Claude, GPT, Amazon Titan) via AWS Bedrock and integrate RAG pipelines using LangChain or Haystack.
  • Build knowledge bases and embedding models for contextual reasoning using vector databases (Pinecone, OpenSearch).
  • Apply memory management techniques for multi-agent orchestration (short-term and long-term memory persistence).
  • Ensure observability and reliability using AWS CloudWatch, X-Ray, and Dynatrace.
  • Implement security best practices (IAM, KMS, encryption) and compliance frameworks (SOC2, GDPR).
  • Build automation frameworks using UiPath or RPA tools to complement AI-driven workflows.
  • Optimize for performance, scalability, and cost efficiency in AWS deployments.
  • Stay current with emerging AI orchestration frameworks, LLM technologies, and cloud-native patterns.

Requirements

What you’ll need
  • 5+ years of experience in software development with a strong focus on AI/ML integration and intelligent automation.
  • 3+ years of hands-on experience building agentic AI solutions and multi-agent orchestration workflows.
  • 5+ years of proficiency in: Backend: Python (FastAPI), .NET Core. Frontend: Angular for UI integration.
  • 3+ years of experience with AWS Agent core, AWS Bedrock, SageMaker, Lambda, Fargate, Step Functions, EventBridge, Glue, S3.
  • 3+ years of strong understanding of ML engineering practices, including model lifecycle management and AI-first SDLC integration.

Benefits

Comp & perks
  • 401K matching
  • health benefits
  • employee stock options
  • paid time off
  • volunteer time off

ATS Keywords

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Hard Skills & Tools
PythonFastAPI.NET CoreAngularAWS EventBridgeAWS LambdaAWS Step FunctionsAWS BedrockUiPathRPA
Soft Skills
collaborationproblem-solvingadaptabilitycommunicationleadership