Senior Lead Software Engineer; Data, Cloud, ML

at  JPMorganChase

JOB DESCRIPTION

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level
As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Investment Bank, Markets Research Technology Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will work on cutting-edge projects such as recommender systems and GenerativeAI applications, helping us industrialize AI/ML models at Production scale. This role is a pure hands-on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role.

REQUIRED QUALIFICATIONS, CAPABILITIES, AND SKILLS

• Formal training or certification on software engineering concepts and proficient advanced experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s), preferably Python
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Overall knowledge of the Software Development Life Cycle
• Proven track record in system design, architecting and developing micro services, distributed systems and data-intensive applications
• Advanced experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies
• Strong coding skills in Python or similar programming language, API and backend development
• Practical experience developing Production-scale Cloud-native AI/ML engineering systems in commercial environments
• Familiarity with Kubernetes, MLOps, Docker and Cloud ML/Data engineering services
• Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds

PREFERRED QUALIFICATIONS, CAPABILITIES, AND SKILLS

• Experience working on recommendation systems, NLP services, or other AI/ML systems
• Practical experience with Kubernetes, EKS, Docker, MLOps, GraphQL
• Prior experience collaborating with data scientists
• Familiarity with modern full-stack development

ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Builds end-to-end data-intensive micro-services, including data pipelines, distributed processing and backend application development
• Designs and implements end-to-end ML engineering solutions, moving experimental models to production scale systems
• Contributes to software engineering communities of practice and events that explore new and emerging technologies
• Adds to team culture of diversity, equity, inclusion, and respect
• Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.
• Designs and implements hands-on solutions while providing technical leadership and mentorship to more junior team members, including managerial responsibilities