AI Products & Platforms Director

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Employee Type

Full-Time

Location

USA (Remote)

Job Type

Brokerage/Product Strategy

Job ID

3315

#WeAreTradeStation

Remote Position - must reside in Florida, Texas, Illinois, New York, New Jersey, Colorado, Idaho, Massachusetts, Michigan, Minnesota, Missouri, North Carolina, South Carolina, Utah or Virginia

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'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. You'll define roadmaps, write requirements, and ship AI capabilities into production—while ensuring platforms are scalable, secure, and compliant.

You're a proven AI product operator who has designed, deployed, and scaled AI solutions in production (ideally in financial services or another regulated environment). You thrive on execution: translating strategy into working systems and measurable business impact.

You will drive delivery across three core areas:

Customer-facing AI experiences for active traders
Internal AI automation to improve speed and efficiency
AI tools for Product Management (prompt libraries, agents, frameworks) to accelerate decision-making

You can navigate SEC/FINRA frameworks, align InfoSec, Legal, and Compliance, and carve a repeatable path to market for AI products—from roadmap vision to hands-on execution.

If you're a hands-on AI builder with strong product management skills, the drive to deliver measurable outcomes, and the ability to navigate the challenges of operating in a regulated brokerage environment, we want to talk to you.

What You'll Be Doing:

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)
Monitoring & 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

The Skills You Bring:

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)
Demonstrated experience embedding AI into customer experiences and internal operations with measurable KPIs

Minimum 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