Lead Software Engineer

Drive significant business impact and tackle a diverse array of challenges that span multiple technologies and applications

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer Python Java at JPMorgan Chase within Consumer and Community Banking’s Operations Technology Voice organization, you will be an integral part of an agile team that enhances, builds, and delivers trusted, market-leading technology products in a secure, stable, and scalable manner. You will apply deep technical expertise and problem-solving methodologies to address challenges spanning multiple technologies and applications while driving significant business impact through your leadership and contributions.

Job responsibilities

Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors

Develops secure and high-quality production code, and reviews and debugs code written by others

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.

Drives decisions that influence the product design, application functionality, and technical operations and processes

Serves as a function-wide subject matter expert in one or more areas of focus

Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience

Hands-on practical experience delivering system design, application development, testing, and operational stability

Advanced in one or more programming language(s)

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.

Ability to tackle design and functionality problems independently with little to no oversight

Experience mentoring and developing mid-level and senior engineers, including setting technical standards and conducting substantive design and code reviews.

Proven ability to influence and communicate effectively with both engineering teams and non-technical senior stakeholders, including written design documentation and executive-level verbal updates.

Working knowledge of secure engineering, data privacy, and controls expectations for systems handling sensitive customer data and recorded interactions.

Experience with CI/CD, infrastructure as code, and automated testing in a regulated enterprise environment.

Preferred qualifications, capabilities and skills

Hands-on experience designing, building, or migrating production IVR / contact center solutions, particularly migrations to Amazon Connect from legacy platforms (e.g., Genesys/PureConnect/Engage, Avaya, Cisco UCCE/CVP, NICE CXone, Twilio Flex).

Deep working knowledge of Amazon Connect core components: Contact Flows, Routing Profiles, Queues, Quick Connects, Hours of Operation, Agent Workspace, and Contact Lens.

Experience integrating Connect with AWS Lambda for contact-flow logic, Amazon Lex (v2) for conversational IVR / intent routing, Amazon Polly for TTS, and Kinesis Video / Data Streams for call recording and real-time event streams.

Familiarity with Connect Streams API, Contact Control Panel (CCP) embedding, and CTI/screen-pop integration into agent desktops or CRMs (e.g., Salesforce Service Cloud, Pega, in-house agent UIs).

Experience building self-service IVR journeys, DTMF and natural-language menus, callback/queue-position features, and intelligent/attribute-based routing.

Practical cloud native experience