AI Solutions Engineer-Wealth Management Marketing

Take AI from a promising idea to a tool that a marketing team uses every day. As an AI Solutions Engineer, you’ll work directly with content and creative teams to tackle repetitive tasks, connect disconnected workflows, and build solutions on the firm’s approved enterprise platforms. You’ll test what works with the people who use these solutions and refine them to meet the demands of real-world production. As an AI Solutions Engineer on the J.P. Morgan Wealth Management Marketing team, you’ll build agents, assistants, automations, and integrations using approved enterprise AI platforms, low-code tools, APIs, and Python scripting. You’ll work directly with the teams using these solutions, evaluate their effectiveness, and partner with technology and product teams to move proven prototypes toward production. Job responsibilities Build AI-powered agents, assistants, automations, and integrations on the firm’s approved enterprise AI platforms. Use low-code agent builders and native connectors, and add custom scripting when needed to extend platform capabilities. Partner with marketing, content, creative, and events teams to identify high-value use cases, quickly turn them into working prototypes, and refine the ones that prove useful. Advocate for solutions with technology and product teams, and partner with them to take solutions from prototype to production—from engineering intake and prioritization through release. Connect AI solutions to the marketing and creative tool stack—including content and asset management, work management, review and approval, and collaboration platforms—through APIs and native connectors. Design and run evaluations by building test sets and measuring output quality and reliability. Use the results to tune knowledge sources, guardrails, model settings, and workflow logic. Document what you build and maintain solutions as platforms and models are updated, including managing access and knowledge sources. Enable users of the AI toolset through training sessions, documentation, office hours, and hands-on support. Work within the firm’s AI governance, model risk, data privacy, and information security requirements, and prepare documentation for required reviews. Required qualifications, capabilities, and skills 3+ years of experience building technical solutions for business teams, such as automations, integrations, internal tools, or AI-powered workflows Bachelor’s degree in a related field Hands-on experience building with large language models, including retrieval over knowledge sources, agents or assistants, tool and API integrations, and output-quality evaluation Working proficiency in Python for scripting, data handling, API calls, and light integration work. A software engineering background is not required, but you should be able to follow documentation, read code, and debug it. Experience with low-code and no-code platforms, including automation and workflow tools and agent builders, and a clear understanding of where these tools reach their limits and code is needed Experience partnering with technology and product teams to move solutions into production, including making the business case and navigating engineering and release processes Ability to turn a loosely defined business problem into a scoped, buildable solution and explain technical trade-offs to nontechnical partners Strong communication and facilitation skills, with experience training or supporting users on new tools Comfort working in a controlled, regulated environment with formal review processes Preferred qualifications, capabilities, and skills 5+ years of experience, including delivering AI or automation solutions within a large enterprise Experience taking AI solutions through model risk management, data governance, or similar review and approval processes Familiarity with marketing and creative agency tools, such as content management, digital asset management, work management, marketing automation, and design platforms JavaScript or TypeScript experience for custom actions in low-code platforms and plugin or web-based tools SQL and relational data skills, and experience importing raw data from platforms such as Snowflake or Databricks into custom dashboards for nontechnical partners Experience with enterprise collaboration and workflow automation platforms, and familiarity with agent development frameworks such as Google’s Agent Development Kit Background in marketing operations, content operations, creative production, or agency workflows