Lead Software Engineer- Python & AWS

As a Lead Cloud Software Engineer at JPMorgan

Chase within the Cloud Financial Management organization, you design and build modern, cloud-native software solutions with a strong focus on cost optimization. This role is hands‑on and requires advanced engineering skills to develop scalable services, data pipelines, and automation that improve cloud efficiency, governance, and performance. You will also apply AI skills and develop/manage AI agents that enable natural‑language querying and analysis of large‑scale cloud financial data.

You will collaborate across teams to deliver best‑in‑class outcomes and accelerate cloud adoption throughout the firm.

Our team delivers comprehensive financial management solutions for optimizing cloud resource usage, cost efficiency, and performance. We focus on leveraging cloud technologies and AI to drive digital transformation and cloud adoption throughout the firm.

• Design, build, and maintain cloud‑native software solutions that optimize resource usage and cost efficiency, with a focus on hands‑on development.
• Develop and maintain engineering and architecture standards, including cloud resource management and governance frameworks.
• Build and maintain pipelines for cost optimization, ensuring efficient, reliable data flow and processing.
• Develop an optimization and recommendation engine to enhance cost efficiency within the Cloud Financial Management organization.
• Collaborate with Product Managers and domain leads to understand their cloud needs and provide guidance on best practices for cloud solution development.
• Leverage AWS services (e.g., S3, EC2, Lambda, Glue) to build scalable and secure cloud solutions, actively engaging in coding, testing, and deployment.
• Utilize AWS Step Functions to automate complex business processes, enhancing operational efficiency.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise‑authorized AI‑assisted development and automation capabilities, to improve the value realized by automation.
• Develop and manage AI agents to support processing and optimization across large volumes of data, including AI‑driven workflow automation.
• Use modern coding productivity tools efficiently (e.g., Git Hub Copilot, Claude Code), and apply AI skills to improve developer workflows and delivery automation.
• Implement governance and security measures to ensure compliance with industry standards.
• Write and analyze Splunk queries to interpret AWS Cloud Trail logs, ensuring robust monitoring, alerting, and security visibility.
• Monitor and optimize the performance, reliability, and scalability of cloud infrastructure and applications.
• Provide training and support to domain teams on cloud engineering principles and AWS technologies.
• Stay up-to-date with industry trends and emerging technologies in cloud computing and software engineering.
• Champion the firm’s culture of diversity, Opportunity, inclusion, and respect.

• Strong knowledge of Python and SQL, with the ability to write efficient and scalable code for data processing and analysis.
• Strong knowledge of AWS, including the ability to design, implement, and operate cloud‑based solutions using services such as S3, EC2, ECS, Lambda, Glue, and related ecosystem services.
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (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 engineers on safe, compliant adoption within delivery practices.
• Strong knowledge of Data Lake or Big Data technologies, with familiarity working with large‑scale data storage and processing solutions.
• Proficiency in Terraform for infrastructure as code to automate provisioning and management of cloud resources.
• Demonstrated ability to design and build resilient systems with strong hands‑on coding and development experience (including code quality, testing, and CI/CD practices).
• Knowledge of building AI skills, workflow automation, and AI agents that can query and analyze large volumes of data efficiently and securely.
• Knowledge of building RESTful APIs in microservices and familiarity with front‑end technologies such as React (Type Script).
• Knowledge of writing Splunk queries to analyze AWS Cloud Trail logs.
• Good to have experience in cost optimization strategies and building pipelines and engines for resource efficiency.