Principal AI Solutions Engineer

#WeAreTradeStation

 

Remote Position - must reside Florida, Texas, Illinois, New York, New Jersey, Alabama, Arizona, Arkansas, Colorado, Connecticut, Delaware, Georgia, Indiana, Kansas, Massachusetts, Missouri, North Carolina, Tennessee, Utah or Wisconsin

 

Who We Are:

 

TradeStation is the home of those born to trade. As an online brokerage firm and trading ecosystem, we are focused on delivering the ultimate trading experience for active traders and institutions. We continuously push the boundaries of what's possible, encourage out-of-the-box thinking, and relentlessly search for like-minded innovators.

 

At TradeStation, we are building an AI-First culture. We expect team members to embrace AI as a core part of their daily workflow, whether that’s using AI to accelerate development, enhance decision-making, improve client outcomes, or streamline internal processes. We hire, grow, and promote people who can harness AI responsibly and creatively. We treat AI as a partner in problem-solving, not just a tool; following our governance standards to ensure AI is used ethically, securely, and transparently. If you join us, you’re joining a culture where AI is how we work.

 

Are you ready to make yourself at home?

 

What We Are Looking For:

We are looking for a Principal AI Solutions Engineer who will be responsible for designing, implementing, and optimizing AI/LLM solutions that drive business value across Brokerage Services Dev. This role

requires deep hands-on expertise in AI/ML systems, strong engineering fundamentals, and the ability to bridge technical implementation with business requirements. This role will work closely with the VP, AI Innovation and Transformation to architect and build production AI systems, collaborate closely with business stakeholders to understand requirements, and establish technical standards for AI/LLM

deployment.

 

What You’ll Be Doing:

Data Platform & BI Integration

Help develop and maintain data models, SQL queries, and analytics workflows in Databricks

Support BI reporting infrastructure including Power BI and Sigma integrations

Implement data quality monitoring, anomaly detection, and automated alerting systems

Partner with EA/Platform teams on data pipeline development and optimization

Technical Architecture & Platform Development

Architect scalable AI solutions leveraging Databricks, Unity Catalog, and modern data platforms

Help design and implement data pipelines, feature engineering workflows, and ML infrastructure

Establish technical patterns and best practices for AI/LLM system development

Build tooling and frameworks that accelerate AI solution delivery across teams

AI/LLM Solution Engineering

Design and implement production-grade AI/LLM systems including RAG pipelines, prompt

engineering frameworks, and evaluation workflows

Build and optimize MCP integrations, AI agent architectures, and LLM orchestration patterns

Develop guardrails, observability systems, and monitoring solutions for AI/LLM applications

Work hands-on with model deployment, fine-tuning, and performance optimization

Business Requirements & Solution Design

Partner with business stakeholders to translate requirements into technical solutions

Conduct technical discovery, assess feasibility, and define solution architectures

Create technical specifications, design documents, and implementation plans

Collaborate with Data Science and ML Engineering teams on model development and deployment

Operational Excellence

Establish observability and monitoring for production AI systems

Implement cost tracking and optimization strategies for compute and serverless resources

Build experimentation frameworks (A/B testing, pilots) and evaluation methodologies

Drive continuous improvement through performance analysis and system optimization

Governance & Risk Management

Implement responsible AI practices including safety, fairness, and privacy controls

Develop model risk management processes and documentation

Establish access governance patterns for Databricks resources and AI platforms

Create technical documentation, runbooks, and knowledge-sharing materials

The Skills You Bring:

Strong software engineering fundamentals with experience building production systems

Deep technical expertise in AI/LLM technologies, including prompt engineering, RAG systems, and agent frameworks

Hands-on experience with Databricks platform (SQL Warehouses, Unity Catalog, MLflow) and data engineering

Proficiency in Python, SQL, and modern ML/AI frameworks and libraries

Experience with cloud platforms and infrastructure as code

Strong understanding of data modeling, pipeline development, and analytics workflows

Familiarity with BI tools (Power BI, Sigma) and data visualization

Experience with Agile development practices and tools (Git, Jira, CI/CD)

Knowledge of experimentation methodologies, A/B testing, and statistical analysis

Understanding of responsible AI principles, model risk management, and governance

Excellent communication skills with ability to explain technical concepts to business stakeholders

Ability to prioritize competing demands, maintain focus on critical path items, and drive projects from conception to production deployment

Strong problem-solving ability and experience working in fast-paced environments

Proven track record of building and deploying production AI/LLM applications

Strong hands-on experience with Databricks, modern data platforms, and cloud infrastructure

Demonstrated ability to work across business and technical stakeholders to deliver impactful solutions

Deep hands-on experience with modern data platforms including data lakes, Delta Lake, Unity Catalog, and Lakehouse architectures preferred

Proven track record building and scaling RAG systems in production environments preferred

Experience implementing Model Context Protocol (MCP) servers and integrations preferred

Experience with prompt engineering frameworks, evaluation systems, and LLM observability tools preferred

Familiarity with AI governance frameworks and responsible AI implementation in enterprise settings preferred

Published work, open-source contributions, or conference presentations related to AI/ML systems preferred

Experience with real-time data processing and stream processing frameworks (Kafka, Spark Streaming) preferred

Knowledge of cost optimization strategies for cloud-based ML workloads and serverless architectures preferred

Minimum Qualifications:

4+ years of experience in software engineering, ML engineering, data engineering, or related technical roles with significant focus on AI/ML systems

Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field; equivalent experience considered

Desired Qualifications:

7+ years of experience in software engineering, ML engineering, or data engineering with at least 3 years focused on production AI/LLM systems

Master's degree or PhD in Computer Science, Machine Learning, Data Science, or related technical field

Databricks Certified Machine Learning Professional or Data Engineer Professional certification

Cloud platform certification (AWS Solutions Architect, Azure AI Engineer, or Google Cloud Professional Machine Learning Engineer)

What We Offer:

Collaborative work environment

Competitive Salaries

Yearly bonus

Comprehensive benefits for you and your family starting Day 1

Unlimited Paid Time Off

Flexible working environment

TradeStation Account employee benefits, as well as full access to trading education materials

Pay Range (US) $160-175K (Countries outside of the US have differing ranges in accordance with local labor markets)

 

TradeStation provides equal employment opportunities to current and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, sexual orientation, age, pregnancy, disability, handicap, citizenship, veteran or marital status, or any other legally recognized status entitled to protection under federal, state, or local anti-discrimination laws.

#LI-Remote