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AVP – Principal AI Engineer

austin, TX

Check who can apply and the requirements below before continuing.

About this opportunity

Jobtailor lists this AVP – Principal AI Engineer opportunity in austin, Texas. Review the employer’s description below for duties, qualifications and application requirements.

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.

Highest-signal resume keywords

AI/ML Solution Development

Cloud Engineering with AWS

Python Programming

Generative AI and LLM Applications

Technical Leadership and Mentoring

Hard Skills

Machine Learning Development

API Design and Development

Microservices Architecture

TensorFlow

PyTorch

Scikit-learn

NLP

RAG Architectures

Deep Learning

Predictive Analytics

Soft Skills

Cross-Functional Collaboration

Technical Communication

Mentoring

Certifications & Qualifications

Master's Degree in Computer Science

Bachelor's Degree in Computer Science

Industry Keywords

Wealth Management

Financial Services

Banking

FinTech

Insurance

Healthcare

Responsible AI Principles

Model Governance

Risk Management

Tools & Technologies

AWS Bedrock

CI/CD Practices

Cloud-Native Applications

AI/ML Frameworks

#J-18808-Ljbffr

Worksite address

austin, TX, 78716, US

Who can apply

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