Lead Software Engineer- Python, AIML, Cloud

We offer an opportunity to shape your career and embark on an exciting journey where you can push the boundaries of what’s possible.

As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Banking – Applied AI/ML team, you are an integral member of an agile group dedicated to enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. As a core technical contributor, you will drive critical technology solutions across multiple technical domains and business functions, supporting the firm’s strategic objectives.

Job Responsibilities

• Design, develop, and troubleshoot software solutions for complex business challenges
• Write secure, high-quality production code and review code from team members
• Identify and automate remediation of recurring issues to improve system stability
• Lead architectural design sessions and provide technical guidance for on-premises and cloud systems
• Promote adoption of new technologies through internal communities of practice
• Foster a culture of diversity, equity, and respect within the team
• Develop and maintain applications using Python and AWS
• Create and review architecture and design deliverables, ensuring best practices are followed
• Integrate AI/ML solutions into domain-specific operations processing systems
• Lead code reviews, design discussions, and agile planning sessions
• Collaborate with Site Reliability Engineering and monitoring teams to ensure system reliability and performance

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Strong experience building and running applications on AWS or other public cloud platforms including Kubernetes.
• Advanced proficiency in Python programming
• Proven experience in system design, application development, testing, and maintaining operational stability
• Skilled in automation, continuous delivery, and the full Software Development Life Cycle
• Experience with data processing pipelines and Directed Acyclic Graphs (DAGs) for machine learning or data workflows
• Demonstrated expertise in cloud, artificial intelligence, and machine learning technologies
• Understanding of IT systems in the financial services industry
• Experience with code reviews and agile methodologies
• Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
• Commitment to continuous learning and creative problem-solving

Preferred Qualifications, Capabilities, and Skills

• Experience with Cloud services, Infrastructure as Code (e.g., Terraform), and containerized application development
• Familiarity with data storage systems such as Postgres and OpenSearch, and AWS services including S3, SageMaker, and Bedrock
• Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps, Large Language Model Operations (LLMOps), and event-driven systems
• Knowledge of security best practices in cloud and application development
• Experience integrating AI/ML models into production environments
• Ability to mentor and guide junior engineers
• Participation in technology events or software engineering communities