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Title: AI Product Platforms Director
Location: Remote
Job Type: Full-Time
Referral Bonus: $4,000 +/-
Candidate Must reside in: FL, TX, IL, NY, NJ, CO, ID, MA, MI, MN, MO, NC, SC, UT, VA
Position Summary
We are seeking an AI Product Platforms Director to translate AI strategy into execution. This role combines product management leadership with hands-on platform delivery, owning the roadmap, requirements, and deployment of AI-driven capabilities.
Reporting to the Senior Director of AI, Data Science & Enterprise Data, this individual will build and scale production-grade AI platforms that are secure, compliant, and highly performant.
The ideal candidate is a hands-on AI product leader with a proven track record of shipping AI/ML products in production—preferably within regulated environments. You are execution-focused, able to translate strategy into systems, and drive measurable business impact.
This role will lead delivery across three key areas:
- Customer-facing AI experiences
- Internal AI-driven automation
- AI tooling for product management and decision-making
Key Responsibilities
- AI Product Strategy & Execution
- Own the full AI product lifecycle from roadmap development and requirements definition to delivery and launch
- Translate business strategy into scalable AI platforms and capabilities
- Define acceptance criteria, manage backlogs, and ensure agile delivery execution
- Platform Development & Implementation
- Build, deploy, and operate AI platforms including LLMs, agent frameworks, and semantic pipelines
- Ensure systems are production-ready with monitoring, performance optimization, and operational guardrails
- Design scalable infrastructure for AI-driven applications
- AI Enablement & Use Case Delivery
- Customer AI: Deliver AI-enhanced experiences within digital platforms
- Operational AI: Implement automations that improve efficiency and scalability across internal workflows
- Product AI Tools: Build prompt libraries, retrieval systems (RAG), and agent frameworks to enhance product management effectiveness
- Experimentation & Scaling
- Design A/B tests and experimentation frameworks to validate AI use cases
- Evaluate proofs of concept (POCs) for viability and scale successful solutions into production
- Drive continuous iteration and improvement of AI products
- Responsible AI & Compliance
- Implement guardrails for fairness, explainability, transparency, and auditability
- Partner with InfoSec, Legal, and Compliance teams to ensure adherence to regulatory standards
- Develop repeatable processes for AI approvals and governance
- Monitoring & Optimization
- Track adoption, performance metrics, cost, latency, and model drift
- Optimize AI systems for reliability, scalability, and efficiency
- Establish feedback loops and retraining strategies
- Cross-Functional Leadership
- Collaborate with Product, Engineering, Data Science, and Operations teams
- Drive enterprise-wide adoption of AI platforms and capabilities
- Communicate progress and outcomes to leadership with a focus on measurable business impact
Required Skills & Experience
Core Competencies
- Hands-on AI Execution: Proven experience designing and deploying AI solutions including LLMs, agents, and automation workflows
- Product Management Expertise: Strong experience with roadmaps, requirements, agile methodologies, and product delivery
- AI/ML Platforms: Familiarity with tools such as AWS (SageMaker, Bedrock), LLM APIs, vector databases, and orchestration frameworks
- Outcome-Oriented Mindset: Ability to define KPIs (adoption, ROI, latency, efficiency) and deliver measurable results
- Experimentation & Scaling: Experience with A/B testing, causal inference, and rapidly scaling validated solutions
- Responsible AI: Understanding of bias mitigation, explainability, monitoring, and model governance
- Enterprise Integration: Experience integrating AI platforms with enterprise data systems (e.g., Snowflake, Databricks) and governance tools
- Collaboration: Strong cross-functional leadership across Product, Engineering, Data, Compliance, and Operations teams
Preferred Experience
- Regulated industry experience (financial services strongly preferred)
- Knowledge of brokerage workflows, trading systems, and financial markets
- Vendor and ecosystem evaluation for AI/fintech tools
- Experience embedding AI into both customer-facing products and internal operations
Qualifications
Experience:
- 7–10 years in product or platform roles
- 5+ years building or operating AI/ML-powered products or automation workflows
- 3–5 years leading cross-functional teams with successful production delivery
Education:
- Bachelor’s degree required
- Advanced degree (Computer Science, Data Science, Financial Engineering, MBA, or similar) preferred
Title: AI Product Platforms Director
Location: Remote
Job Type: Full-Time
Referral Bonus: $4,000 +/-
Candidate Must reside in: FL, TX, IL, NY, NJ, CO, ID, MA, MI, MN, MO, NC, SC, UT, VA
Position Summary
We are seeking an AI Product Platforms Director to translate AI strategy into execution. This role combines product management leadership with hands-on platform delivery, owning the roadmap, requirements, and deployment of AI-driven capabilities.
Reporting to the Senior Director of AI, Data Science & Enterprise Data, this individual will build and scale production-grade AI platforms that are secure, compliant, and highly performant.
The ideal candidate is a hands-on AI product leader with a proven track record of shipping AI/ML products in production—preferably within regulated environments. You are execution-focused, able to translate strategy into systems, and drive measurable business impact.
This role will lead delivery across three key areas:
- Customer-facing AI experiences
- Internal AI-driven automation
- AI tooling for product management and decision-making
Key Responsibilities
- AI Product Strategy & Execution
- Own the full AI product lifecycle from roadmap development and requirements definition to delivery and launch
- Translate business strategy into scalable AI platforms and capabilities
- Define acceptance criteria, manage backlogs, and ensure agile delivery execution
- Platform Development & Implementation
- Build, deploy, and operate AI platforms including LLMs, agent frameworks, and semantic pipelines
- Ensure systems are production-ready with monitoring, performance optimization, and operational guardrails
- Design scalable infrastructure for AI-driven applications
- AI Enablement & Use Case Delivery
- Customer AI: Deliver AI-enhanced experiences within digital platforms
- Operational AI: Implement automations that improve efficiency and scalability across internal workflows
- Product AI Tools: Build prompt libraries, retrieval systems (RAG), and agent frameworks to enhance product management effectiveness
- Experimentation & Scaling
- Design A/B tests and experimentation frameworks to validate AI use cases
- Evaluate proofs of concept (POCs) for viability and scale successful solutions into production
- Drive continuous iteration and improvement of AI products
- Responsible AI & Compliance
- Implement guardrails for fairness, explainability, transparency, and auditability
- Partner with InfoSec, Legal, and Compliance teams to ensure adherence to regulatory standards
- Develop repeatable processes for AI approvals and governance
- Monitoring & Optimization
- Track adoption, performance metrics, cost, latency, and model drift
- Optimize AI systems for reliability, scalability, and efficiency
- Establish feedback loops and retraining strategies
- Cross-Functional Leadership
- Collaborate with Product, Engineering, Data Science, and Operations teams
- Drive enterprise-wide adoption of AI platforms and capabilities
- Communicate progress and outcomes to leadership with a focus on measurable business impact
Required Skills & Experience
Core Competencies
- Hands-on AI Execution: Proven experience designing and deploying AI solutions including LLMs, agents, and automation workflows
- Product Management Expertise: Strong experience with roadmaps, requirements, agile methodologies, and product delivery
- AI/ML Platforms: Familiarity with tools such as AWS (SageMaker, Bedrock), LLM APIs, vector databases, and orchestration frameworks
- Outcome-Oriented Mindset: Ability to define KPIs (adoption, ROI, latency, efficiency) and deliver measurable results
- Experimentation & Scaling: Experience with A/B testing, causal inference, and rapidly scaling validated solutions
- Responsible AI: Understanding of bias mitigation, explainability, monitoring, and model governance
- Enterprise Integration: Experience integrating AI platforms with enterprise data systems (e.g., Snowflake, Databricks) and governance tools
- Collaboration: Strong cross-functional leadership across Product, Engineering, Data, Compliance, and Operations teams
Preferred Experience
- Regulated industry experience (financial services strongly preferred)
- Knowledge of brokerage workflows, trading systems, and financial markets
- Vendor and ecosystem evaluation for AI/fintech tools
- Experience embedding AI into both customer-facing products and internal operations
Qualifications
Experience:
- 7–10 years in product or platform roles
- 5+ years building or operating AI/ML-powered products or automation workflows
- 3–5 years leading cross-functional teams with successful production delivery
Education:
- Bachelor’s degree required
- Advanced degree (Computer Science, Data Science, Financial Engineering, MBA, or similar) preferred
To Apply for this Job Click Here
Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.
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