Note: The job is a remote job and is open to candidates in USA. TradeStation is an online brokerage firm focused on delivering the ultimate trading experience for active traders and institutions. They are seeking a Principal AI Solutions Engineer responsible for designing, implementing, and optimizing AI/LLM solutions that drive business value across Brokerage Services Dev, collaborating closely with business stakeholders and establishing technical standards for AI/LLM deployment.
Responsibilities
- 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
- 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
- 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
- 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
- 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
- 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
Skills
- 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
- 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
- Proven track record building and scaling RAG systems in production environments
- Experience implementing Model Context Protocol (MCP) servers and integrations
- Experience with prompt engineering frameworks, evaluation systems, and LLM observability tools
- Familiarity with AI governance frameworks and responsible AI implementation in enterprise settings
- Published work, open-source contributions, or conference presentations related to AI/ML systems
- Experience with real-time data processing and stream processing frameworks (Kafka, Spark Streaming)
- Knowledge of cost optimization strategies for cloud-based ML workloads and serverless architectures
Benefits
- 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
Company Overview
Company H1B Sponsorship