AI Engineer Jobs at JPMorganChase with Visa Sponsorship
AI Engineer jobs at JPMorganChase span consumer banking, institutional services, and risk infrastructure, with visa sponsorship available for qualified candidates in this function. If you're targeting a role here, the company has a consistent track record of supporting international hires through the full petition process.
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Get Access To All JobsJob Description
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Software Engineer at JPMorganChase within the AI/ML Data Platforms team, you will be a key member of an agile team responsible for enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. You will drive meaningful business impact through hands-on engineering leadership, applying deep technical expertise and structured problem-solving to address complex challenges across multiple technologies and applications. In this role, you will help design and deliver agentic AI platforms and large language model (LLM)-enabled services for enterprise use cases. You will contribute to architecture and engineering decisions, build cloud-native services on AWS, and improve system quality through strong evaluation, observability, and operational excellence practices. You will also raise engineering standards through high-quality code reviews, clear documentation, and effective collaboration across teams.
Job Responsibilities
- Provide technical guidance and direction to business and engineering teams by partnering with external teams to align on priorities, unblock delivery, and drive successful engineering outcomes.
- Develop secure, high-quality production code and lead code reviews; review, debug, and improve code written by others to raise overall engineering quality.
- Drive architecture and design decisions that influence product design, application functionality, and technical operations (including SDLC practices).
- Serve as a subject matter expert in one or more focus areas, helping teams make sound technical trade-offs and resolve complex problems.
- Evaluate and introduce leading-edge technologies where appropriate, influencing peers and decision-makers with clear rationale and risk/benefit analysis.
- Build and operate production-grade LLM applications, including agentic patterns and tool integrations for enterprise use cases.
- Design and deliver cloud-native services on AWS using containers and serverless architectures, with strong attention to scalability and operational resilience.
- Implement retrieval-augmented generation (RAG) solutions, including embeddings, semantic search, and practical context engineering to improve answer quality and control.
- Build reliable service APIs and integrations with a focus on security, performance, and maintainability.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required Qualifications, Capabilities, And Skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Strong Python engineering skills; experience with PyTorch or TensorFlow
- Expertise working with Vector storage systems and designing memory for Agents
- Expertise developing long running agents that run autonomously using tools, skills and human in the loop
- Proven experience deploying LLM-backed services to production (APIs, microservices)
- Deep MLOps experience, including CI/CD, monitoring, incident response, and model governance
- Cloud-native AI deployment experience (AWS or Azure), with cost and performance optimization
- Demonstrated commitment to responsible AI practices and operational excellence
- Strong communication and collaboration skills, working across product, risk, legal, and compliance teams
- Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
- Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
Preferred Qualifications, Capabilities, And Skills
- Experience with fine-tuning, adapters, or custom evaluation frameworks.
- Background operating AI systems in regulated environments (finance, healthcare, etc.).
- Experience with prompt engineering and LLM orchestration.
- Knowledge of safety filters, audit logging, and explainability in production systems.
- Experience mentoring senior engineers and leading architecture discussions.
- Demonstrated ability to influence technical roadmaps and priorities.
About us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 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. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About The Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Job Description
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Software Engineer at JPMorganChase within the AI/ML Data Platforms team, you will be a key member of an agile team responsible for enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. You will drive meaningful business impact through hands-on engineering leadership, applying deep technical expertise and structured problem-solving to address complex challenges across multiple technologies and applications. In this role, you will help design and deliver agentic AI platforms and large language model (LLM)-enabled services for enterprise use cases. You will contribute to architecture and engineering decisions, build cloud-native services on AWS, and improve system quality through strong evaluation, observability, and operational excellence practices. You will also raise engineering standards through high-quality code reviews, clear documentation, and effective collaboration across teams.
Job Responsibilities
- Provide technical guidance and direction to business and engineering teams by partnering with external teams to align on priorities, unblock delivery, and drive successful engineering outcomes.
- Develop secure, high-quality production code and lead code reviews; review, debug, and improve code written by others to raise overall engineering quality.
- Drive architecture and design decisions that influence product design, application functionality, and technical operations (including SDLC practices).
- Serve as a subject matter expert in one or more focus areas, helping teams make sound technical trade-offs and resolve complex problems.
- Evaluate and introduce leading-edge technologies where appropriate, influencing peers and decision-makers with clear rationale and risk/benefit analysis.
- Build and operate production-grade LLM applications, including agentic patterns and tool integrations for enterprise use cases.
- Design and deliver cloud-native services on AWS using containers and serverless architectures, with strong attention to scalability and operational resilience.
- Implement retrieval-augmented generation (RAG) solutions, including embeddings, semantic search, and practical context engineering to improve answer quality and control.
- Build reliable service APIs and integrations with a focus on security, performance, and maintainability.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required Qualifications, Capabilities, And Skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Strong Python engineering skills; experience with PyTorch or TensorFlow
- Expertise working with Vector storage systems and designing memory for Agents
- Expertise developing long running agents that run autonomously using tools, skills and human in the loop
- Proven experience deploying LLM-backed services to production (APIs, microservices)
- Deep MLOps experience, including CI/CD, monitoring, incident response, and model governance
- Cloud-native AI deployment experience (AWS or Azure), with cost and performance optimization
- Demonstrated commitment to responsible AI practices and operational excellence
- Strong communication and collaboration skills, working across product, risk, legal, and compliance teams
- Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
- Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
Preferred Qualifications, Capabilities, And Skills
- Experience with fine-tuning, adapters, or custom evaluation frameworks.
- Background operating AI systems in regulated environments (finance, healthcare, etc.).
- Experience with prompt engineering and LLM orchestration.
- Knowledge of safety filters, audit logging, and explainability in production systems.
- Experience mentoring senior engineers and leading architecture discussions.
- Demonstrated ability to influence technical roadmaps and priorities.
About us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 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. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About The Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
See all 82+ AI Engineer Jobs at JPMorganChase
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Engineer Jobs at JPMorganChase.
Get Access To All JobsTips for Finding AI Engineer Jobs at JPMorganChase
Tailor your resume to financial AI
JPMorganChase AI Engineer roles emphasize applied ML in fraud detection, algorithmic trading, and risk modeling. Frame your experience around production systems and measurable outcomes, not research prototypes. Generic ML resumes get filtered before they reach a hiring manager.
Target internal mobility and return offers
JPMorganChase actively converts interns and contractors into full-time sponsored hires. If you're on OPT, a co-op or summer internship gives you a direct path to sponsorship before your 60-day grace period ever becomes a concern.
Search verified sponsoring employers on Migrate Mate
Filter AI Engineer openings at JPMorganChase using Migrate Mate, which surfaces roles by visa type and filing history. This saves you from applying to postings where sponsorship eligibility is ambiguous or has to be confirmed mid-process.
Clarify your visa category before the offer
JPMorganChase sponsors H-1B, E-3, and H-1B1 visa depending on your nationality. Raise your visa status early with the recruiter so the right petition type is queued. Waiting until the offer stage can add weeks if the legal team has to reclassify your filing.
Prepare a degree equivalency letter proactively
USCIS requires AI Engineer petitions to demonstrate specialty occupation status. If your degree is from outside the U.S. or is in an adjacent field like physics or statistics, get a credential evaluation done before your I-129 is filed, not after an RFE arrives.
Understand where PERM fits your long-term plan
JPMorganChase files EB-2 and EB-3 PERM-based green card petitions for retained AI Engineering staff. DOL's PERM process typically runs 12 to 18 months before the I-140 stage, so aligning your H-1B clock with that timeline matters from your first year.
Frequently Asked Questions
Does JPMorganChase sponsor H-1B visas for AI Engineers?
Yes, JPMorganChase sponsors H-1B visas for AI Engineers. The company's legal team manages the I-129 petition process, including premium processing where timelines require it. Because JPMorganChase operates at scale across financial services and technology, its immigration infrastructure is well-established for this function compared to smaller firms navigating sponsorship for the first time.
Which visa types does JPMorganChase commonly use for AI Engineer roles?
JPMorganChase sponsors H-1B, H-1B1 visa, and E-3 visas for AI Engineers depending on your nationality. Australian citizens are eligible for the E-3, which has no lottery and allows biennial renewals. H-1B1 applies to Chilean and Singaporean nationals. For longer-term pathways, the company also pursues EB-2 and EB-3 Green Card sponsorship for retained engineering staff.
What qualifications does JPMorganChase expect for AI Engineer roles?
Most AI Engineer roles at JPMorganChase require a bachelor's degree or higher in computer science, engineering, applied mathematics, or a closely related field. Hands-on experience with large-scale ML pipelines, model deployment in production environments, and familiarity with financial data domains like risk, fraud, or market analytics strengthens your application significantly. Advanced degrees are common but not universally required.
How do I apply for AI Engineer jobs at JPMorganChase?
You can browse and apply for AI Engineer openings at JPMorganChase directly through their careers portal or through Migrate Mate, which filters roles by visa sponsorship type so you can confirm eligibility before applying. When submitting your application, be specific about your visa status in any early screening questions. Recruiters at JPMorganChase route candidates to the appropriate legal team once an offer is extended.
How do I plan my timeline around JPMorganChase's H-1B sponsorship process?
USCIS opens H-1B registration in early March each year, with the lottery drawing shortly after. If selected, your employer files the full petition by the end of June for an October 1 start date. If you're on OPT, make sure your STEM extension or existing OPT authorization covers you through that gap. Starting conversations with your JPMorganChase recruiter in the fall or winter before the cap season gives enough runway to prepare.