AI Lead Solutions Engineer
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Role details
Tech stack
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Job description
- Embed with our advisors, business teams, and product partners to discover and frame high-value AI/ML opportunities
- Rapidly prototype and build agentic AI and LLM-powered solutions full-stack and end-to-end to demonstrate value quickly
- Harden and scale solutions with our core AIML team after initial validation
- Own solutions end-to-end during the engagement, including problem framing, build, demo, iteration, and hand-off to production
- Act as the primary technical translator between business and product stakeholders and our engineering team
- Shape opportunities into funded, well-scoped workstreams
- Balance speed of iteration with our engineering, Responsible AI, and control standards, including guardrails, evaluation, and observability
- Feed reusable patterns, skills, and learnings back into our platform so each engagement compounds
- Contribute to our GenAI education and knowledge-sharing efforts
- Mentor junior engineers on solutioning and delivery
- Champion our culture of diversity, opportunity, inclusion, and respect
Technologies:
- Agentic AI
- AI
- Backend
- CI/CD
- Claude Code
- Cloud
- Copilot
- GitHub
- LLM
- Machine Learning
- Python
- RAG
- AWS
- Network
Requirements
- Formal training or certification in AI/ML engineering concepts, with applied experience
- Advanced Python and full-stack or generalist engineering ability, including backend, data, and lightweight front-end development
- Strong software engineering practices, including testing, code review, and version control
- Fluency with AI coding tools such as Claude Code or GitHub Copilot as part of day-to-day development
- Practical experience with Large Language Models, including prompt engineering, RAG, and/or agentic frameworks
- Hands-on experience taking solutions from prototype to production, including CI/CD, containerisation, and cloud-native deployment
- Proven ability to work directly with non-technical stakeholders, including eliciting needs, framing problems, demoing, influencing, and building trust
- Comfort with ambiguity and the ability to switch context quickly across multiple problem domains, stakeholders, and engagements
- Product mindset with the ability to prioritise by user value and outcomes
- Commercial acumen to identify measurable business value, define success metrics, and build the case to fund and scale solutions
- Masters degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent applied experience
- Preferred: industry-recognised cloud or GenAI certification
- Preferred: prior forward-deployed, solutions-engineering, consulting, or client-facing engineering experience
- Preferred: openness to periodic on-site embedding with business teams and occasional international travel
- Preferred: experience within financial services, particularly wealth, private banking, or asset management
- Preferred: experience designing or contributing to AI governance, model validation, or guardrail frameworks
- Preferred: familiarity with JPM-internal AI/ML infrastructure and governance for internal candidates
About the company
We are J.P. Morgan, a global leader in financial services, providing strategic advice and products to prominent corporations, governments, wealthy individuals, and institutional investors. Our first-class business in a first-class way approach guides how we serve clients and build trusted, long-term partnerships. This Vice President role sits within our International Private Bank Technology Artificial Intelligence and Machine Learning team, reporting to the Head of AI, IPB Tech. We value diversity, inclusion, and equal opportunity, and we offer an environment where our Asset & Wealth Management businesses deliver investment management and private banking solutions across global markets.
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