Pay
$154K–$225K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,958 postings in the last year. Stated ranges, not salaries paid.
Executive Product Solutions Director (Data, AI & GenAI Architecture)
New York, NY, United States
Live, first seen by us 1 day ago- Pay
- Pay not listedSimilar roles state $154K–$225K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingLead Technical Account Managers and shape customer platform adoption strategies
Design scalable cloud-native architectures for RAG, agentic and ML systems
Architect data platforms and pipelines for secure, reliable AI applications
Establish MLOps and LLMOps governance, monitoring and evaluation practices
Route client feedback to Product teams to influence roadmap and priorities
From the employer’s posting
lead and enable Technical Account Managers (TAMs), shape customer-centric platform adoption strategies
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 (data lakes/lakehouses, ETL/ELT, embedding generation, vector database integrations)
Establish MLOps/LLMOps governance: CI/CD patterns, model monitoring, drift detection, evaluation (including hallucination testing)
Manage the collection of client feedback and ensure structured, actionable delivery of feedback to Product teams
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Nov 3, 20261 day ago
- Recorded sightings
- 2
- Last seen by us
- Nov 4, 2026
- Reposted
- once since Sep 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 7 and day 53.
From 7,797 similar postings that came down. Coming down is not always a hire.
JPMorgan Chase is hiring
413 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Leadership hiring is steady
- Takes jobs down at a usual pace
- 3% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- Docker
- Kafka
- Kubernetes
- Snowflake
- Spark
- GCP
Where the posting names them
- Cloud platforms: AWS, Azure, and/or GCP. - Data engineering: SQL, Python, Apache Spark; familiarity with data warehouses/lakehouse ecosystems (for example; Snowflake, Databricks); event streaming (for example; Kafka). - DevOps/MLOps: Docker, Kubernetes, CI/CD tooling, model/version management, and evaluation benchmarks (including LLM evaluation approaches).
- Strong ability to operate as a senior technical and strategic advisor communicating trade-offs clearly to technical and non-technical stakeholders. - Cloud platforms: AWS, Azure, and/or GCP. - Data engineering: SQL, Python, Apache Spark; familiarity with data warehouses/lakehouse ecosystems (for example; Snowflake, Databricks); event streaming (for example; Kafka).
- Data engineering: SQL, Python, Apache Spark; familiarity with data warehouses/lakehouse ecosystems (for example; Snowflake, Databricks); event streaming (for example; Kafka). - DevOps/MLOps: Docker, Kubernetes, CI/CD tooling, model/version management, and evaluation benchmarks (including LLM evaluation approaches). Preferred qualifications, capabilities, and skills
Your next step
Complete your application on jpmc.fa.oraclecloud.com. The employer’s form will show what is required.
Applying through Oracle Recruiting
- Applying starts by asking for your email address.
- Each employer sets which files it accepts, so read the note beside the upload field.
Already applied? Track this application
Has JPMorgan Chase posted this job before?
Yes. We’ve followed one other Executive Product Solutions Director (Data, AI & GenAI Architecture) job there since September 2026. It is still up.
About the role
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
- Median yearly pay, May 2025
- $175,140
- Expected change, 2025 to 2035
- 15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Job description
Unlock your potential as a leader in product solutions and Generative AI architecture. In this role, you will lead and enable Technical Account Managers (TAMs), shape customer-centric platform adoption strategies, and define scalable GenAI/ML system architectures across the Firmwide Data and AI Platform product cluster. You will act as the technical bridge between business strategy, data science, and cloud software engineering balancing innovation with enterprise requirements such as cost, latency, data privacy, and compliance.
As a Executive Product Solutions Director in the Firmwide Data and AI Platform team, and as a senior leader, you will craft complex, end-to-end solutions, assess and govern risk, capture market opportunities, and establish repeatable processes that allow teams to continuously deliver value to customers in a fast-paced, collaborative environment.
Job responsibilities
- Advise Product Solutions teams on solutioning and adoption of new and existing client-facing products and capabilities, crafting complex solutions and assessing risk to enhance customer experience.
- Partner with TAMs (Technical Account Managers) to identify, shape, and capture market opportunities; develop solution strategies that scale across customers and use cases.
- Lead the strategic development of end-to-end product solution strategies and processes across a cluster of products (Data and AI Platforms), ensuring consistency, quality, and delivery velocity.
- Manage the collection of client feedback and ensure structured, actionable delivery of feedback 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 (data lakes/lakehouses, ETL/ELT, embedding generation, vector database integrations) to support secure, reliable AI applications.
- Evaluate, select, and integrate foundation models (for example; GPT-family, Claude, open-source LLMs), enabling model orchestration via frameworks (for example; LangChain, LlamaIndex) or custom microservices.
- Establish MLOps/LLMOps governance: CI/CD patterns, model monitoring, drift detection, evaluation (including hallucination testing), and AI safety guardrails suitable for production.
- Ensure solutions adhere to enterprise security and compliance requirements, including data privacy, RBAC, and intellectual property protection.
- Lead architecture design reviews and decision documentation (for example; ADRs), mentor engineering teams, and translate technical trade-offs into business value.
Required qualifications, capabilities, and skills
- 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 clients’ 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 communicating trade-offs clearly to technical and non-technical stakeholders.
- Cloud platforms: AWS, Azure, and/or GCP.
- Data engineering: SQL, Python, Apache Spark; familiarity with data warehouses/lakehouse ecosystems (for example; Snowflake, Databricks); event streaming (for example; Kafka).
- DevOps/MLOps: Docker, Kubernetes, CI/CD tooling, model/version management, and evaluation benchmarks (including LLM evaluation approaches).
Preferred qualifications, capabilities, and skills
- Hand on experience developing solutions specifically for Data and AI Platforms
- Deep practical experience with GenAI patterns and tooling: RAG, vector databases (for example; Pinecone, Milvus, pgvector), fine-tuning, and multi-agent systems.
- Self-starter, comfortable operating with the ambiguity and helping stand up a new team/function (defining operating model, playbooks, governance, and repeatable delivery mechanisms).
Source details
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- Pay
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- Location & working pattern
New York, NY, United States
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- Work authorization
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