Sr Lead Software Engineer

JPMorganChase; Jersey City (NJ); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorgan Chase is seeking a Senior Lead Software Engineer within Corporate Technology Data Strategy & Architecture to drive secure, scalable data-driven software in a fast-paced agile team. You will own end-to-end design, build AI-enabled systems, and mentor engineers while aligning with firmwide SDLC and governance.

You will apply deep technical expertise to tackle data-intensive challenges across multiple technologies, ensuring secure handling, reliability, and performance in production

Qualifications

• Formal training or certification in software engineering with 5+ years of applied experience.
• Hands-on experience building LLM-based apps and agentic systems in production.
• Proficiency in Python and/or Java.
• Experience with large-scale data processing, microservices, API design, and Kafka.
• Knowledge of relational/NoSQL data stores, vector stores, and data lakes.
• Familiarity with caching, observability tools, and orchestration (Airflow/Temporal).
• CI/CD, TDD, automation and full SDLC discipline.
• Strong Agile, resiliency, and security practices.
• Cloud-native engineering experience (AWS/Azure/GCP).
• Experience leading AI-assisted dev tools adoption and governance.
• Understanding of responsible AI use and data handling.

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.

Skills

Python

Java

LLM-based apps

Data processing

API design

CI/CD

Cloud-native

Observability tools

Security best practices

AI governance

Tools

Kafka

Airflow

Temporal

Docker

Kubernetes

Databricks

Snowflake

Jenkins

Job description

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.

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 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 systems
• Awareness of AI risk and regulatory considerations relevant to AI use in financial decision-making

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.