AI Products & Platforms Director

About the role

We’re seeking an AI Product Platforms Director to turn TradeStation’s AI strategy into reality. Reporting to the Sr. Director of AI, Data Science & Enterprise Data, this role combines product management leadership with hands-on platform execution.

Responsibilities

• Own the AI product lifecycle — define roadmaps, write requirements, and deliver AI-powered features and platforms from concept through launch
• Drive the three legs of AI delivery:
• Customer-facing AI — embed AI into trading platforms and tools for differentiated active trader experiences
• Internal operational AI — design and deploy automations that reduce inefficiency and increase scale
• Product Management enablement — build prompt libraries, retrieval/semantic search, and agent frameworks that accelerate PM decision-making
• Build and operate AI platforms — configure, deploy, and run LLMs, agent frameworks, and semantic pipelines in production with monitoring, guardrails, and incident readiness
• Experimentation & POC scaling — design A/B tests and controlled experiments, triage proofs-of-concept for technical/business viability, and scale the most impactful into production
• Responsible AI & compliance — implement fairness, explainability, transparency, and auditability guardrails; align with InfoSec, Legal, and Compliance to create repeatable approval playbooks (SEC/FINRA aware)
• Misson & optimization — track adoption, quality, drift, and cost/latency tradeoffs; plan retrains and continuous improvements to AI models and platforms
• Influence adoption across the enterprise — ensure AI platform capabilities are adopted across product lines and business units
• Report outcomes, not activity — communicate milestones and progress to leadership tied directly to measurable business impact
• Continuous improvement & horizon scanning — stay ahead of emerging AI technologies, industry trends, and platform best practices to keep TradeStation on the cutting edge

Requirements

• Hands-on AI Builder & Stack Fluency — deep experience designing, prototyping, and deploying AI automations, LLMs, agents, and prompt-driven workflows, with familiarity in AWS AI/ML services (e.g., SageMaker, Bedrock), Copilot/ChatGPT, vector databases/RAG, and orchestration frameworks such as Databricks MCP
• Demonstrated success operationalizing AI across internal product and engineering workflows — for example, championing Spec-Driven Development (SDD) practices augmented by AI to enable scalable, auditable specification pipelines that reduce ambiguity, accelerate sprint planning, and improve requirement traceability at the enterprise level
• Product Management Discipline — roadmaps, requirements, acceptance criteria, launch readiness, and iterative delivery in agile environments
• Outcome-Oriented — skilled at defining KPIs (adoption, ROI, latency/SLOs, approval cycle times) and driving teams to measurable impact
• Regulatory Navigation — proven ability to align with SEC/FINRA, InfoSec, Legal, and Compliance to accelerate approvals while ensuring safe deployment
• Experimentation, POC Triage & Scaling — hands-on experience with A/B testing, causal methods, and rapid assessment of POCs to scale winners into production
• Responsible AI & Monitoring — bias mitigation, explainability, auditability logs, incident response, drift detection, and feedback loops for continuous improvement
• Collaboration & Enterprise Data Integration — ability to partner across Product, Data Science, Enterprise Data, Ops, and Engineering; experience integrating AI platforms with enterprise data platforms (e.g., Snowflake, Databricks) and governance tools (Collibra, Alation, Informatica)
• Ecosystem & Vendor Awareness — ability to evaluate and integrate third-party AI/fintech solutions that accelerate delivery
• Brokerage Domain Knowledge (preferred) — understanding of equities, options, futures, and brokerage workflows (back office, middle office, risk, compliance)

Qualifications

• 7–10 years in product/platform roles, including 5+ years building or operating AI/ML-powered products or large-scale workflow automations in regulated environments
• 3–5 years leading cross-functional delivery teams (PM/Eng/Data); proven record of shipping to production with quantifiable impact