Job Description
If you take ownership of outcomes in production — not just implementation — and thrive on turning ambiguous requirements into stable, well-modeled service designs, this role was built for you.
As a Senior Lead Software Engineer at JPMorganChase within the Corporate Artificial Intelligence and Machine Learning Data Platforms – Machine Learning Center of Excellence, you will design, build, and optimize high-performance, low-latency distributed systems that serve as the backbone of our machine learning and data infrastructure. You will collaborate across engineering, data science, and platform teams to deliver resilient, cloud-native solutions that enable the firm to operate at the forefront of AI-driven innovation. Your work will directly shape the reliability, scalability, and performance of systems that process critical data across the enterprise, and your voice will carry weight in the architectural and engineering decisions that define how the platform evolves. You will have meaningful latitude to influence architecture, engineering standards, and reliability posture across services, with expectations and recognition aligned to senior-level impact.
Job responsibilities
- Architect and implement low-latency, high-throughput Java Spring Boot–based distributed services using object-oriented principles, delivering production-grade performance with strong, well-defined APIs
- Design and build resilient, cloud-native service architectures with high-availability requirements from 99.9% to 99.999%, leveraging AWS compute, messaging, streaming, database, and storage services including Managed Streaming for Apache Kafka (MSK), Simple Queue Service (SQS), S3, Elastic Container Service (ECS), Elastic Kubernetes Service (EKS), Lambda, Kinesis Video/Data Streams, Relational Database Service (RDS), DynamoDB, and Redshift
- Develop and maintain infrastructure-as-code solutions using Terraform and/or CloudFormation to support scalable, repeatable, and auditable cloud deployments
- Implement and continuously improve observability solutions — including alerting, monitoring, and reporting — using Datadog, Dynatrace, and Splunk to deliver actionable production intelligence across microservices platforms
- Translate ambiguous or evolving requirements into stable, well-modeled service designs, clearly articulating engineering tradeoffs to both technical and non-technical stakeholders
- Lead technical design reviews, establish engineering best practices, and drive adoption of standards that improve platform operability, reliability, and maintainability
- Own production outcomes end-to-end — identifying and resolving performance bottlenecks, reliability gaps, and scalability constraints through automation and runbook-driven operations
- Partner with machine learning engineers and data scientists to understand platform requirements and deliver robust, production-ready engineering solutions
- Mentor and provide technical guidance to engineers across the team, fostering a culture of ownership, continuous learning, and engineering excellence
- Drive adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes — including AI-assisted code review, test acceleration, release readiness, and incident analysis — while establishing measurable validation standards and promoting reuse of proven patterns within the software development lifecycle toolchain
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience, with very strong Java development skills using object-oriented principles and significant experience with Spring Boot
- Demonstrated experience designing and tuning for low-latency processing in production distributed systems
- Hands-on experience leveraging AWS services including MSK (Kafka), SQS, S3, ECS, EKS, Lambda, Kinesis Video/Data Streams, RDS, DynamoDB, and Redshift in large-scale, resilient service architectures
- Practical experience implementing alerting, monitoring, and reporting solutions using Datadog, Dynatrace, and/or Splunk in production-grade environments
- Strong engineering fundamentals including API design, testing discipline, and debugging in production contexts
- Proficiency in one or more modern programming languages — with heavy emphasis on Java — writing clean, maintainable, object-oriented, and testable code
- Strong experience with containerization and orchestration technologies, including Docker and Kubernetes
- Demonstrated ability to communicate engineering tradeoffs clearly to both technical and non-technical stakeholders
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools for coding, code review, test acceleration, and 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 and outputs, and adherence to resiliency and security expectations, with experience coaching engineers on compliant usage patterns and controls
Preferred qualifications, capabilities, and skills
- Deep familiarity with low-latency, highly transactional architectures and advanced usage of AWS managed services — particularly Kinesis Video/Data Streams — for real-time processing, distributed event handling, and efficient data storage and retrieval
- Expertise designing and automating observability and reporting workflows using Datadog, Dynatrace, and Splunk to deliver actionable monitoring and production intelligence across microservices platforms
- Experience with modern delivery practices including continuous integration and delivery, infrastructure-as-code, and containerized deployments that support reliable service delivery at scale
- Experience with Terraform and/or CloudFormation for building and maintaining cloud infrastructure in an enterprise environment
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
Skills Required
- Formal training or certification in software engineering concepts
- 5+ years of applied software engineering experience
- Very strong Java development skills using object-oriented principles
- Significant Spring Boot experience
- Experience designing and tuning low-latency production distributed systems
- Hands-on experience with AWS MSK, SQS, S3, ECS, EKS, Lambda, Kinesis Video/Data Streams, RDS, DynamoDB, and Redshift
- Experience implementing production alerting, monitoring, and reporting with Datadog, Dynatrace, and/or Splunk
- Strong API design, testing, and production debugging skills
- Proficiency in one or more modern programming languages, with heavy emphasis on Java
- Strong experience with Docker and Kubernetes
- Ability to communicate engineering tradeoffs to technical and non-technical stakeholders
- Experience leading enterprise-authorized AI-assisted software development practices
- Understanding of responsible AI use, data sensitivity, secure input/output handling, resiliency, and security controls
- Deep familiarity with low-latency, highly transactional architectures
- Advanced AWS managed-services experience, particularly Kinesis Video/Data Streams
- Expertise automating observability and reporting workflows with Datadog, Dynatrace, and Splunk
- Experience with continuous integration and delivery, infrastructure as code, and containerized deployments
- Experience with Terraform and/or CloudFormation
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.
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Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
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Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
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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