Sr Lead Software Engineer

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.

• Develops secure, high-quality production code for data-intensive applications

requirements through deployment and operational stability

• Drives technical decisions that influence application design, functionality,

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+

• Experience with LLM orchestration frameworks
• Hands-on experience with model serving infrastructure or managed endpoints

• Leads end-to-end design and implementation of complex software features, from

• 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

• 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

• Executes creative software solutions, including design, development, and

• Mentors and coaches junior and mid-level engineers, conducting code reviews

• Contributes to firmwide frameworks, tools, and SDLC practices as an engaged

• 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.

• 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

• Deep experience with large-scale data processing, microservices, API design,

• Working knowledge of relational and NoSQL databases, vector stores, and data

• 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

• Strong understanding of agile methodologies, application resiliency, and

• 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.

• Familiarity with AI evaluation and observability practices: evals frameworks,

• Understanding of agentic design patterns and how to constrain agent autonomy

• 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

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.

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.