Senior Lead Software Engineer - AI/ML/Databricks/Python

JPMorganChase; Atlanta (GA); On-site; USD 140,000 - 180,000; Full time

Job summary

JPMorganChase in Atlanta, GA seeks a Senior Lead Software Engineer focused on AI/ML and Databricks to advance trusted, scalable technology products within Consumer and Community Banking. You will lead agile teams, guide engineers, and implement AI-assisted development practices to improve quality, speed, and security across the SDLC.

The role requires expertise in Python, PySpark, Databricks, AWS, and responsible AI usage, with hands-on experience delivering production-grade systems and

Qualifications

• Formal training or certification on software engineering concepts.
• 5+ years of applied experience in software engineering.
• Experience delivering system design and production code.
• Experience with cloud-native architectures.

Responsibilities

• Provides technical guidance to business and technical teams.
• Develops secure, high-quality production code and reviews code.
• Drives AI-assisted engineering practices across teams for code quality and delivery speed.
• Applies SDLC tooling and AI-assisted development capabilities to improve automation.
• Influences product design, application functionality, and technical operations.
• Acts as a subject matter expert in one or more focus areas.
• Contributes to engineering community and best practices.

Skills

Python

PySpark

Databricks

Agentic AI/GenAI

AWS

LLMs

Secure coding

Software design

Education

Software engineering certification

Tools

AI-assisted development tools

Cloud native tools

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 - AI/ML/Databricks/Python at JPMorganChase within the Consumer and Community Banking, 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

• 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) including PYthon, PySpark, Databricks, Agentic AI/GenAI, AWS and LLM
• 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
• Practical cloud native experience

Preferred qualifications, capabilities, and skills

Emerging technologies