DescriptionWe 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/AI/ML Backend Engineer at JPMorgan Chase within the Chief Data & Analytics Office (CDAO), you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading and cutting edge technology products in a secure, stable, and scalable way. This technology includes AI/ML Platform Solutions using python based REST APIs, SDKs, & Generative AI; all deployed on the public cloud using modern standards and patterns. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
- Develops secure high-quality production code, and reviews and debugs code written by others.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
- Work closely with the Product team to design, build and deliver capabilities in agile sprints.
- Collaborate with cross-functional teams, including data scientists, software engineers, and designers, to integrate with various applications and products.
- Adds to team culture of diversity, equity, inclusion, and respect.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, cloud deployment strategies, and operational stability.
- Experience working with Python, Generative AI, cloud based ML platforms, AWS SageMaker, Azure OpenAI, Google Vertex, Databricks, Terraform, Jenkins, DynamoDB, Cassandra etc.
- Proficiency in automation and continuous delivery methods.
- Proficient in all aspects of the Software Development Life Cycle.
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, etc.)
- Practical cloud native experience.
Preferred qualifications, capabilities, and skills
- Knowledge of data analytics tools will be a plus.
- Ability to adapt to new technologies and learn quickly in a fast-paced environment.
