AVP – Principal AI Engineer

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Austin (TX)

On-site

USD 150,000 - 210,000

Full time

2 days ago

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Job summary

LPL Financial is seeking a senior AI/ML software engineer to design, develop, and deploy production-grade AI/ML solutions that support business objectives and advisor experience.

You will build AI-powered applications using LLMs, generative AI, RAG architectures, and ML models; lead end-to-end lifecycle; collaborate with Wealth Management, Risk, Product, and Engineering to translate requirements into scalable solutions.

Qualifications

Minimum of 8 years of software engineering, AI/ML engineering, or machine learning development experience.
Proven track record of building and deploying production AI solutions in complex enterprise environments.
Strong hands-on programming expertise in Python.

Responsibilities

Design, develop, and deploy production-grade AI/ML solutions supporting business objectives and advisor experience.
Architect and build AI-powered applications using LLMs, generative AI, and RAG architectures.
Lead end-to-end software engineering lifecycle for AI solutions, including design, development, testing, deployment, monitoring, and optimization.
Partner with Wealth Management, Operations, Risk, Marketing, Product, and Engineering teams to translate business requirements into scalable technical solutions.
Develop and deliver AI-enabled products, platforms, and tools that improve advisor productivity and client experience.

Skills

Python Programming

AI/ML Engineering

NLP & ML

LLMs & Generative AI

RAG Architectures

APIs & Microservices

Cloud-native Architecture

Model Serving

Observability & Security

Education

Master's Degree in Computer Science

Bachelor's Degree in Computer Science

Tools

AWS Bedrock

CI/CD

Cloud-Native Apps

AI/ML Frameworks

Job description

Design, develop, and deploy production-grade AI/ML solutions supporting LPL Financial’s business objectives and advisor experience
Architect and build AI-powered applications using LLMs, generative AI, agentic workflows, RAG architectures, and machine learning models
Lead the end-to-end software engineering lifecycle for AI solutions, including design, development, testing, deployment, monitoring, and optimization
Partner with Wealth Management, Operations, Risk, Marketing, Product, and Engineering teams to identify AI use cases and translate business requirements into scalable technical solutions
Develop and deliver AI-enabled products, platforms, and tools that improve advisor productivity, operational efficiency, and client experience
Build and maintain cloud-native AI solutions using AWS services, including Bedrock and related AI/ML technologies
Design and implement APIs, microservices, and platform services enabling reusable and scalable AI capabilities
Establish engineering best practices for AI development, model evaluation, deployment, observability, security, and responsible AI
Collaborate with data, engineering, and architecture teams to ensure solutions are secure, compliant, performant, and aligned with enterprise standards
Evaluate emerging AI technologies, frameworks, and tooling and recommend adoption opportunities
Provide technical leadership, mentoring, and architectural guidance to engineers
Present technical solutions, architecture decisions, and AI innovation opportunities to business and technology stakeholders

Requirements

Minimum of 8 years of software engineering, AI/ML engineering, or machine learning development experience
Proven track record of building and deploying production AI solutions in complex enterprise environments
Strong hands-on programming expertise in Python
Experience with TensorFlow, PyTorch, scikit-learn, LangChain, or similar AI/ML frameworks
Experience designing, developing, and deploying Generative AI and machine learning solutions
Experience with LLM-based applications, NLP, RAG architectures, AI agents, model serving, or related AI technologies
Strong cloud engineering experience with AWS, Azure, or GCP
Experience deploying scalable AI/ML workloads and cloud-native applications
Experience in highly regulated industries such as Wealth Management, Financial Services, Banking, FinTech, Insurance, Healthcare, or similar
Understanding of supervised learning, unsupervised learning, deep learning, NLP, recommendation systems, and predictive analytics
Experience delivering AI solutions from concept through production deployment, monitoring, and optimization
Strong software engineering fundamentals, including APIs, microservices, scalable architectures, testing, and CI/CD practices
Experience translating business requirements into technical solutions
Knowledge of responsible AI principles, model governance, security, privacy, and risk management
Demonstrated technical leadership, mentoring, and cross-functional influence
Master's degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field

Core Competencies

Demonstrates expertise in designing, developing, and deploying AI/ML solutions, with a strong focus on cloud-native applications and scalable architectures. Proven ability to lead technical teams, mentor engineers, and translate business requirements into effective AI strategies.

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