What are the responsibilities and job description for the Software Engineer III - Infrastructure and Backend position at JPMorgan Chase?
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Corporate Sector AI2 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.
The Applied Innovation of AI (AI2) team is an elite machine learning group strategically located within the CTO office of JP Morgan Chase. AI2 tackle business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning for Software, Cybersecurity and Technology Infrastructure. The team partners closely with all lines of business and engineering teams across the firm to execute long-term projects in these areas that require significant machine learning development to support JPMC businesses as they grow. We are looking for excellent full stack software engineers to help us with the design, development, deployment, delivery, and maintenance of AI products to our clients. In this role, you will be working with other engineers & research scientists in building & maintaining software and infrastructure that supports our team in developing and delivering disruptive AI products that serve our customers in production
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 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
- Collaborate with data scientists and research/machine learning engineers to deliver products to production.
- Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation)
- 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
- Build backend interfaces leveraging modern web stacks
- Build and automate and maintain our AI/ML data pipelines & workstream from data analysis, experimentation, model training, model evaluation, deployment, operationalization, and tuning to visualization
- Improve and maintain our automated CI/CD pipeline while collaborating with our stakeholders, various testing partners and model contributors
- Increase our deployment velocity, including the process for deploying models and data pipelines into production
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3 years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in Python Programming, OOP, Databases and Big Data
- Experience with REST API, Cloud, Micro services, and other web technologies
- Experience in AWS cloud and services (S3, Lambda, Aurora, ECS, EKS, SageMaker, Bedrock, Athena, Secrets Manager, Certificate Manager etc.)
- 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 DevOps/MLOps experience provisioning and maintaining infrastructure leveraging some of the following: Terraform, Ansible, AWS CDK, CloudFormation
- Experience in some of the following technologies Hadoop, PySpark, AWS Cloud, AWS DynamoDB, AWS Lambda, Terraform
- Experience in containerization and infrastructure as code Docker/Kubernetes/Terraform
- Experience with CI/CD pipelines example Jenkins/Spinnaker
Preferred qualifications, capabilities, and skills
- Familiar with monitoring tools such as Prometheus, Grafana, Splunk and Datadog
- Strong commitment to development best practices and code reviews
- Strong interpersonal skills; able to work independently as well as in a team
- Experience with deep learning frameworks such as TensorFlow or Pytorch
- Experience with data labelling, validation, provenance and versioning
- Any cloud certifications
