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 and Investment Bank Markets Research Technology, 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 challenging Cloud-native data, backend engineering, and Artificial Intelligence/Machine Learning engineering, helping us industrialize AI/ML models at production enterprise scale. This role is a technical hands-on engineering role. Experience with data science/ML modeling is advantageous but not essential to this role

 

Job responsibilities 

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problemsCreates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systemsProduces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code developmentBuilds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOpsDesigns and implements data engineering solutions, leveraging modern big data technologies   Contributes to software engineering communities of practice and events that explore new and emerging technologiesAdds to team culture of diversity, opportunity, inclusion, and respect

Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.

 

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 10+ years proficient applied experienceHands-on practical experience in system design, application development, testing, and operational stabilityProficient in coding in one or more languages (Python preferably) Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languagesOverall knowledge of the Software Development Life CycleProven track record in system design, architecting and developing microservices, distributed systems and data-intensive applicationsExperience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies        Practical experience developing Production-scale Cloud-native data engineering solutions in commercial environments   Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena, ECS, EKS) and MLOps stack   Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds 

 

Preferred qualifications, capabilities, and skills

Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sectorExperience working on recommendation systems, LLM applications or other AI/ML systems Practical experience with Kubernetes, EKS, Docker, MLOpsPrior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases   Prior experience collaborating with data scientists