AVP, Principal AI Engineer

What you will do

• Design, develop, and deploy production-grade AI/ML solutions aligned to business objectives and advisor experience.
• Architect and build AI-powered applications using modern technologies such as LLMs, generative AI, agentic workflows, RAG architectures, and machine learning models.
• Own 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 high-value AI use cases and translate 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 on AWS, including Bedrock and related AI/ML technologies.
• Design and implement APIs, microservices, and platform services to enable reusable, scalable AI capabilities across the enterprise.
• Establish best practices for AI development, model evaluation, deployment, observability, security, and responsible AI.
• Collaborate with data, engineering, and architecture teams to support secure, compliant, performant solutions aligned with enterprise standards.
• Evaluate emerging AI technologies, frameworks, and tooling, and recommend adoption opportunities.
• Provide technical leadership, mentoring, and architectural guidance, contributing to the growth of a future AI engineering team.
• Present architecture decisions, technical solutions, and AI innovation opportunities to business and technology stakeholders.

Core technologies

Python, TensorFlow, PyTorch, scikit-learn, LangChain, LLMs, generative AI, agentic workflows, RAG architectures, machine learning models, AWS, Bedrock, Azure, GCP, APIs, microservices, observability, security, responsible AI, plus AWS AI services including Bedrock, SageMaker, Textract, and Comprehend. Also includes vector databases, embeddings, knowledge graphs, LLM-based applications, NLP, AI agents, LLM orchestration frameworks, MLOps, model lifecycle management, monitoring, Spark, Hadoop, and Databricks.

Qualifications

• Minimum 8 years of software engineering, AI/ML engineering, or machine learning development experience, with a proven record of building and deploying production AI solutions in complex enterprise environments.
• Strong hands-on programming expertise in Python and experience with modern AI/ML frameworks including TensorFlow, PyTorch, scikit-learn, and LangChain (or similar).
• Experience delivering Generative AI and machine learning solutions, including LLM-based applications, NLP, RAG architectures, AI agents, and model serving.
• Strong cloud engineering experience with AWS, Azure, or GCP, including deploying scalable AI/ML workloads and cloud-native applications.
• Experience in highly regulated industries such as Wealth Management, Financial Services, Banking, FinTech, Insurance, or Healthcare, with governance, security, risk, and compliance requirements.
• Master’s degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field.

Benefits

• 401K matching
• Health benefits
• Employee stock options
• Paid time off
• Volunteer time off
• More