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 JPMorgan Chase within the Corporate Technology Data Strategy & Architecture organization, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Develops secure, high-quality production code for data-intensive applications and platforms, and reviews and debugs code written by others
- Leads end-to-end design and implementation of complex software features, from requirements through deployment and operational stability
- Drives technical decisions that influence application design, functionality, performance, and reliability
- Builds and maintains agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls appropriate for regulated financial services environments
- Implements LLM-based applications including RAG pipelines, embedding workflows, vector store integrations, and model serving infrastructure
- Owns observability, evaluation, and safety of production AI systems — including prompt monitoring, output validation, cost tracking, and latency optimization
- Identifies and executes opportunities to automate remediation of recurring issues and improve operational stability
- Executes creative software solutions, including design, development, and technical troubleshooting to solve complex and ambiguous problems
- Mentors and coaches junior and mid-level engineers, conducting code reviews and sharing engineering best practices
- Contributes to firmwide frameworks, tools, and SDLC practices as an engaged member of the engineering community
- 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
- Hands-on experience building and shipping LLM-based applications and agentic systems with tool use, memory, and multi-step reasoning in production environments
- Advanced proficiency in one or more programming languages, particularly Python and/or Java
- Deep experience with large-scale data processing, microservices, API design, and event streaming (Kafka)
- Working knowledge of relational and NoSQL databases, vector stores, and data lake architectures
- Experience with caching technologies (Redis, MemCached), observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
- Proficiency in CI/CD, test-driven development, automation, and all aspects of the Software Development Lifecycle
- Strong understanding of agile methodologies, application resiliency, and security best practices
- Practical cloud-native engineering experience (AWS, Azure, or GCP)
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
Preferred qualifications, capabilities, and skills
- Experience with LLM orchestration frameworks
- Hands-on experience with model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI)
- Familiarity with AI evaluation and observability practices: evals frameworks, red-teaming, prompt drift detection, and cost/latency monitoring
- Understanding of agentic design patterns and how to constrain agent autonomy in high-stakes financial workflows
- Experience with modern data platforms such as Databricks or Snowflake
- Hands-on experience with Spark/PySpark and big data processing at scale
- Knowledge of the financial services industry and its technology system
- Awareness of AI risk and regulatory considerations relevant to AI use in financial decision-making
About Us
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
- Production experience building and shipping LLM-based applications and agentic systems with tool use, memory, and multi-step reasoning
- Advanced proficiency in Python and/or Java
- Experience with large-scale data processing, microservices, API design, and Kafka event streaming
- Working knowledge of relational and NoSQL databases, vector stores, and data lake architectures
- Experience with Redis or Memcached, Dynatrace, Splunk, Grafana, Airflow, and Temporal
- Proficiency in CI/CD, test-driven development, automation, and the software development lifecycle
- Strong understanding of agile methodologies, application resiliency, and security best practices
- Practical cloud-native engineering experience with AWS, Azure, or GCP
- Experience leading enterprise-authorized AI-assisted software development tools and validating AI outputs for correctness, performance, and security
- Understanding of responsible AI use, data sensitivity, secure input and output handling, resiliency, and security controls
- Experience coaching senior engineers or leads on compliant AI usage patterns and controls
- Experience with LLM orchestration frameworks
- Experience with model-serving infrastructure or managed endpoints such as AWS Bedrock or Azure OpenAI
- Familiarity with AI evaluation, red-teaming, prompt drift detection, and cost and latency monitoring
- Understanding of agentic design patterns and constraining agent autonomy in high-stakes financial workflows
- Experience with Databricks or Snowflake
- Hands-on experience with Spark, PySpark, and large-scale big data processing
- Knowledge of the financial services industry and related technology systems
- Awareness of AI risk and regulatory considerations for financial decision-making
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 — Health coverage is considered comprehensive, including medical, dental, and vision, alongside wellness and mental health resources. Some locations add onsite health centers and related wellbeing support.
-
Retirement Support — Retirement offerings include a 401(k)-type savings plan and related financial benefits, with options such as employee stock purchase participation. Financial planning resources are also highlighted to support long-term savings.
-
Parental & Family Support — Paid parental leave of 16 weeks for birth or adoption is available for all parents. Child care and back-up child care resources further reinforce family support.
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.
Gallery
.png){kind=logo}
