AVP, AI Solutions Engineer

LPL Financial•New York, NY

6d•$146,900 - $244,900•Hybrid

About The Position

We are seeking a highly skilled Individual Contributor (IC) to design and implement agentic AI solutions on the LPL Data Experience (LDX) platform. This role is ideal for a self-driven engineer who thrives in a fast-paced environment, learns quickly, and delivers innovative solutions with minimal guidance. You will build AI-first, agentic frameworks that automate data governance, exception tracking, reconciliation processes, and lifecycle management across multiple domains. These solutions will integrate seamlessly into LDX, enabling users to review exceptions, configure rules, and visualize reconciliation results through intuitive UI components. This is a hands-on development role—you will own the design, coding, deployment, and optimization of AI-driven workflows on AWS, leveraging modern orchestration frameworks, LLM-based intelligence, and ML engineering practices integrated into the SDLC.

Requirements

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.

Nice To Haves

Familiarity with LLMs (Claude, GPT, Titan) and RAG pipelines using LangChain, Haystack, and vector databases.
Strong understanding of data governance principles, lifecycle management, and compliance frameworks.
Experience implementing security best practices for AI workflows.
Hands-on experience with Infrastructure as Code (Terraform) and CI/CD pipelines.
Familiarity with observability tools (CloudWatch, Dynatrace, X-Ray).
Experience leveraging AI-powered developer tools (Cursor, GitHub Copilot).
Experience building automation frameworks using UiPath or RPA tools.

Responsibilities

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.