AI Lead Solutions Engineer -Forward Deployed

Posted Yesterday
Be an Early Applicant
2 Locations
Hybrid
Expert/Leader
Financial Services
We’re one of the world’s biggest technology-driven companies
The Role
Embed with business teams to discover high-value AI opportunities; rapidly prototype and build LLM/agentic solutions end-to-end; harden and hand off production-ready systems; serve as technical translator, mentor junior engineers, and ensure Responsible AI, observability, and scalable patterns.
Summary Generated by Built In

We're looking for a hands-on, business-facing AI engineer who thrives at the intersection of technology and the front line. Join the ranks of top talent at one of the world's most influential companies.

As an AI Solutions Engineer (Forward Deployed) - Vice President at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you will be deployed directly into business contexts to identify where AI can create value, then design, build, and ship the solutions that realise it. You will operate at the front of the team's engagement model: turning ambiguous, surfacing opportunities into scoped, working agentic AI and machine learning solutions, and partnering with the core AIML team to productionise and scale what proves out.

This is a Vice President-level role and an integral part of the IPB Tech AIML team, reporting to the Head of AI, IPB Tech.

Job responsibilities
  • Embeds with IPB advisors, business teams, and product partners (e.g. across Investment, Client experience, and surfacing IPB-first use cases) to discover and frame high-value AI/ML opportunities
  • Rapidly prototypes and builds agentic AI and LLM-powered solutions full-stack and end-to-end (backend, data, and lightweight interfaces as needed) to demonstrate value quickly, then hardens and scales them with the core AIML team
  • Owns solutions end-to-end during the engagement: problem framing, build, demo, iteration, and hand-off to production
  • Acts as the primary technical translator between business/product stakeholders and the engineering team, shaping opportunities into funded, well-scoped workstreams
  • Balances speed of iteration with the team's engineering, Responsible AI, and control standards (guardrails, evaluation, observability)
  • Feeds reusable patterns, skills, and learnings back into the team's platform so each engagement compounds
  • Contributes to the team's GenAI education and knowledge-sharing, and mentors junior engineers on solutioning and delivery
  • Champions the firm's culture of diversity, Opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
  • Formal training or certification on AI/ML engineering concepts and  applied experience
  • Advanced Python and full-stack / generalist engineering ability - backend, data, and lightweight front-end - to ship a working end-to-end solution, with modern software engineering practices (testing, code review, version control)
  • Fluent with AI coding tools (e.g., Claude Code, GitHub Copilot) as a core part of day-to-day development, with the judgement to know when to lean on them and when not to
  • 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 - eliciting needs, framing problems, demoing, influencing, and building trust across technical and business audiences
  • Comfort with ambiguity and the ability to switch context quickly across multiple problem domains, stakeholders, and engagements; a bias to ship and learn while maintaining engineering quality
  • Product mindset: prioritises by user value and outcomes, with the judgement to decide what to build, what to cut, and what "good enough to prove value" looks like
  • Commercial acumen: spots where AI creates measurable business value, frames success metrics, and builds the case to fund and scale what works
  • Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent applied experience)
Preferred qualifications, capabilities, and skills
  • Industry-recognised cloud / GenAI certification (e.g., AWS Certified Generative AI Developer - Professional, or similar)
  • Prior forward-deployed, solutions-engineering, consulting, or client-facing engineering experience
  • Openness to periodic on-site embedding with business teams and occasional international travel, as engagements benefit from it
  • Experience within financial services, particularly wealth, private banking, or asset management
  • Experience designing or contributing to AI governance, model validation, or guardrail frameworks
  • Familiarity with JPM-internal AI/ML infrastructure and governance for internal candidates
About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
  
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
About the TeamJ.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.​

Skills Required

  • Formal training or certification on AI/ML engineering concepts and applied experience
  • Advanced Python and full-stack/generalist engineering ability (backend, data, lightweight front-end) with testing, code review, and version control
  • Fluent with AI coding tools (e.g., Claude Code, GitHub Copilot)
  • 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 (eliciting needs, framing problems, demoing, influencing)
  • Comfort with ambiguity, ability to switch context quickly, and bias to ship while maintaining engineering quality
  • Product mindset and commercial acumen to prioritise user value, define success metrics, and build business cases
  • Master's degree in Computer Science, Data Science, Engineering, or related quantitative field (or equivalent applied experience)
  • Industry-recognised cloud / GenAI certification (e.g., AWS Certified Generative AI Developer) or similar
  • Prior forward-deployed, solutions-engineering, consulting, or client-facing engineering experience
  • Openness to periodic on-site embedding with business teams and occasional international travel
  • Experience within financial services, particularly wealth, private banking, or asset management
  • Experience designing or contributing to AI governance, model validation, or guardrail frameworks
  • Familiarity with JPM-internal AI/ML infrastructure and governance (for internal candidates)

JPMorganChase Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.

  • Healthcare Strength Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
  • Retirement Support A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
  • Leave & Time Off Breadth Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.

JPMorganChase Insights

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The Company
HQ: New York, NY
289,097 Employees
Year Founded: 1799

What We Do

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.

Why Work With Us

Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.

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