Lead Software Engineer - Python - GenAI

JPMorgan Chase; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase in Plano, TX is seeking a Lead Software Engineer to drive design and delivery of GenAI-powered platforms in a fast-paced corporate technology environment.

You will lead an agile team spanning architecture, ML/AI enablement, and productionizing models, with emphasis on security, scalability, and reliability in financial services. The role requires deep Python/Java, microservices, Kubernetes, and experience delivering large-scale distributed systems.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years applied experience.
• The successful candidate demonstrates deep distributed-systems engineering expertise in Python/Java plus strong platform, delivery, and production-operability discipline; Recent hands-on software development experience in large-scale distributed systems, primarily Python and modern microservices.
• Strong Python experience for AI/ML engineering, automation, model operationalization, and agentic AI services, including tool integration, monitoring, telemetry, and governance; Strong experience with REST APIs and service-oriented / microservices architecture
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Experience developing in Linux environments.
• Strong Kubernetes orchestration experience (building, deploying, and operating production services).
• Messaging expertise with Kafka, MQ, or similar platforms.
• Experience with backend infrastructure patterns (e.g., load balancing, autoscaling; Experience with NoSQL databases such as Cassandra; Experience with log analytics / observability tools (e.g., ELK, Splunk).
• Strong SDLC knowledge and agile ways of working, including CI/CD, application resiliency, security, testing, and operational stability; Strong communication skills and proven ability to influence across senior technology and business stakeholders.
• AI/ML platform exposure (MLOps, feature engineering, model hosting/operationalization; AWS and/or hybrid on-prem + cloud); Agentic AI experience: building and operating LLM-driven agents with tool integration, monitoring/telemetry, and governance/audit considerations.

Responsibilities

• Architect and implement resilient, scalable, fault-tolerant, low-latency services and drive target-state architecture.
• Design and deploy services that integrate with enterprise systems; ensure functional, performance, scalability, security, governance, and auditability requirements are met.
• Lead and mentor the development team in a high-pressured delivery environment; manage multiple deliverables across business groups and strengthen stakeholder relationships.
• Collaborate with LOB users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues.
• Build and mature capabilities that execute ML pipelines for fraud detection and risk assessment; support modeling teams in implementation and tooling.
• Productionalize models built by data scientists, including validation readiness and quality controls prior to live usage.
• Drives team adoption of enterprise-authored AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authored AI-assisted development and automation capabilities, to improve the value realized by automation.
• Design and own reusable ML platform components (e.g., feature-store patterns, delivery pipelines) and establish monitoring/alerting for performance, scalability, availability, and reliability.
• Build agentic AI services to automate and enhance engineering and model-ops workflows (tool-using agents, orchestration, state management, and audit-ready traceability).
• Define and implement guardrails and evaluation approaches for agentic AI in production (quality, safety, latency, and cost).

Skills

Python

Java

Microservices

REST APIs

Kubernetes

AI/ML engineering

CI/CD

Security & governance

Distributed systems

Linux

MLOps

Agile / SDLC

Tools

Kafka

ELK

Splunk

Cassandra

Job description

Lead Software Engineer - Python - GenAI

Plano, TX, United States

Job Information

• Job Identification 210786802

• Job Category Software Engineering

• Business Unit Corporate Sector

• Posting Date 10/08/2026, 11:38 AM

• Locations 8181 Communications Pkwy Bldg F, Plano, TX, 75024, US

• Job Schedule Full time

• Job Shift Day

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Corporate Sector – Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.

Job responsibilities

• This role spans architecture, hands‑on delivery, and ML/AI enablement in production. Architect and implement resilient, highly scalable, fault‑tolerant, low‑latency services and drive target‑state architecture.

• Design and deploy services that integrate with enterprise systems; ensure functional, performance, scalability, security, governance, and auditability requirements are met.

• Lead and mentor the development team in a high‑pressured delivery environment; manage multiple deliverables across business groups and strengthen stakeholder relationships.

• Collaborate with LOB users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues.

• Build and mature capabilities that execute ML pipelines for fraud detection and risk assessment; support modeling teams in implementation and tooling.

• Productionalize models built by data scientists, including validation readiness and quality controls prior to live usage.

• Drives team adoption of enterprise‑authorized AI‑assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI‑assisted code review/refactoring, test strategy acceleration, incident/root‑cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise‑authorized AI‑assisted development and automation capabilities, to improve the value realized by automation.

• Design and own reusable ML platform components (e.g., feature‑store patterns, delivery pipelines) and establish monitoring/alerting for performance, scalability, availability, and reliability.

• Build agentic AI services to automate and enhance engineering and model‑ops workflows (tool‑using agents, orchestration, state management, and audit‑ready traceability).

• Define and implement guardrails and evaluation approaches for agentic AI in production (quality, safety, latency, and cost).

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience; Hands‑on practical experience delivering system design, application development, testing, and operational stability

• The successful candidate demonstrates deep distributed‑systems engineering expertise in Python/Java plus strong platform, delivery, and production‑operability discipline; Recent hands‑on software development experience in large‑scale distributed systems, primarily Python and modern microservices.

• Strong Python experience for AI/ML engineering, automation, model operationalization, and agentic AI services, including tool integration, monitoring, telemetry, and governance; Strong experience with REST APIs and service‑oriented / microservices architecture.
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

• Experience developing in Linux environments.

• Strong Kubernetes orchestration experience (building, deploying, and operating production services).

• Messaging expertise with Kafka, MQ, or similar platforms.

• Experience with backend infrastructure patterns (e.g., load balancing, autoscaling; Experience with NoSQL databases such as Cassandra; Experience with log analytics / observability tools (e.g., ELK, Splunk).

• Strong SDLC knowledge and agile ways of working, including CI/CD, application resiliency, security, testing, and operational stability; Strong communication skills and proven ability to influence across senior technology and business stakeholders.

• AI/ML platform exposure (MLOps, feature engineering, model hosting/operationalization; AWS and/or hybrid on‑prem + cloud); Agentic AI experience: building and operating LLM‑driven agents with tool integration, monitoring/telemetry, and governance/audit considerations.

Preferred qualifications, capabilities, and skills

• AWS Certification(s) - and/or Working Knowledge

• AI Certifications(s) - and/or Working Knowledge

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 (https://careers.jpmorgan.com/us/en/how-we-hire/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.