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Senior Engineering Manager
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Mechanical Engineer
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Senior Controls Software Engineer
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Vice President - Java Lead for Investment Banking Advisory Technology
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Lead Software Engineer
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Senior Technical Support Engineer- Global Financial Crimes
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JPMC page

Lead Software Engineer

Jersey City, NJ, United States

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Job details

Experience: Formal training or certification on software engineering concepts and 5+ years applied experience
Posting language: English
Posted: Nov 4, 2026

Original 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 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

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.

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

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More about this job

Skills

Problem solving
Troubleshooting
Root cause analysis
Test automation
Software development
Programming languages
Python
Oracle Java
Process data
Microservices
API development
Apache Kafka
NoSQL
Redis
Dynatrace
Splunk
Grafana
Apache Airflow
CI/CD
Agile
AWS
Microsoft Azure
Google Cloud
Software development tools
Coaching
Databricks
Snowflake
Apache Spark
PySpark
Decision making
Transaction processing
Child care
Mental health
Compensation and benefits

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