Executive Product Solutions Director (Data, AI & GenAI Architecture)

JPMorgan Chase & Co. • New York, NY

3d • $166,250 - $260,000

About The Position

As an Executive Product Solutions Director in JPMorganChase’s Firmwide Data and AI Platform team, you will lead and enable Technical Account Managers (TAMs), shape customer-centric platform adoption strategies, and define scalable GenAI and machine learning architectures across the Firmwide Data and AI Platform product cluster. You will bridge business strategy, data science, and cloud software engineering while balancing innovation with enterprise requirements such as cost, latency, data privacy, and compliance.

As a senior leader, you will craft complex end-to-end solutions, assess and govern risk, capture market opportunities, and establish repeatable processes that enable teams to continuously deliver customer value in a fast-paced, collaborative environment. The role includes advising product-solutions teams, developing scalable adoption strategies, incorporating structured client feedback into product roadmaps, and leading architecture reviews and engineering-team mentorship.

You will design cloud-native GenAI and ML systems, including RAG and agentic workflows; architect data platforms and pipelines; evaluate and integrate foundation models; and establish production-ready MLOps/LLMOps governance, monitoring, evaluation, and safety practices. Solutions must meet enterprise security and compliance requirements, including data privacy, role-based access control, and intellectual property protection.

Requirements

• 8+ years of experience or equivalent expertise leading and developing solutions across multiple teams and a cluster of products.
• Demonstrable experience structuring and handling complex solutions for business problems to meet client needs.
• Extensive experience facilitating internal platform adoption activities and developing and optimizing strategies and processes.
• Strong ability to operate as a senior technical and strategic advisor and communicate trade-offs clearly to technical and non-technical stakeholders.
• Experience with cloud platforms such as AWS, Azure, and/or GCP.
• Data engineering skills including SQL, Python, and Apache Spark; familiarity with data warehouse/lakehouse ecosystems such as Snowflake or Databricks; and event streaming such as Kafka.
• DevOps/MLOps skills including Docker, Kubernetes, CI/CD tooling, model/version management, and evaluation benchmarks, including LLM evaluation approaches.

Nice To Haves

• Hands-on experience developing solutions specifically for Data and AI Platforms.
• Deep practical experience with GenAI patterns and tooling, including RAG, vector databases such as Pinecone, Milvus, or pgvector, fine-tuning, and multi-agent systems.
• Self-starter comfortable operating amid ambiguity and helping stand up a new team or function, including defining its operating model, playbooks, governance, and repeatable delivery mechanisms.

Responsibilities

• Advise Product Solutions teams on solution design and adoption of new and existing client-facing products and capabilities, crafting complex solutions and assessing risk to enhance customer experience.
• Partner with Technical Account Managers (TAMs) to identify, shape, and capture market opportunities and develop solution strategies that scale across customers and use cases.
• Lead the strategic development of end-to-end product solution strategies and processes across the Data and AI Platforms product cluster, ensuring consistency, quality, and delivery velocity.
• Manage the collection of client feedback and ensure its structured, actionable delivery to Product teams to influence roadmap and prioritization.
• Design scalable, cloud-native architectures for Generative AI systems, including Retrieval-Augmented Generation (RAG), agentic workflows, and traditional machine learning solutions.
• Architect data platforms and pipelines, including data lakes/lakehouses, ETL/ELT, embedding generation, and vector database integrations, to support secure and reliable AI applications.
• Evaluate, select, and integrate foundation models, including GPT-family, Claude, and open-source LLMs, and enable model orchestration through frameworks such as LangChain or LlamaIndex, or custom microservices.
• Establish MLOps/LLMOps governance, including CI/CD patterns, model monitoring, drift detection, evaluation such as hallucination testing, and production-appropriate AI safety guardrails.
• Ensure solutions adhere to enterprise security and compliance requirements, including data privacy, RBAC, and intellectual property protection.
• Lead architecture design reviews and decision documentation such as ADRs, mentor engineering teams, and translate technical trade-offs into business value.

Benefits

• Competitive total rewards package, including base salary and, for eligible roles, commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.
• Additional benefits and programs based on eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed