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 AWSCreate 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 SkillsFormal 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