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
- Designs and develops enterprise applications using Java and Spring Boot, with a strong focus on the Rules Engine
- Builds and supports high throughput, low latency applications which leverage state of the art machine learning architectures, and which are deployed in AWS
- Powers personalized experiences across Chase Consumer & Community Banking channels, to help weave a user experience that includes traditional banking services with other services in the Travel, Merchant Offer Shopping, and Dining spaces
- 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
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Strong Experience with Rule’s Engines such as Sapiens, JBoss Drools or IBM Operational Decision Manager (ODM – formerly ILOG)
- Hands on experience with authoring rules comprising of guided rules, guided decision tables, rule flows, excel based rules
- Proven track record in implementing microservices applications using Java, SpringBoot and integrating with Rule’s Engine
- Solid fundamentals and experience in containers (docker ecosystem), container orchestration systems [Kubernetes, ECS], DAG 2 [Airflow, Kubeflow etc.]
- Solid understanding of agile methodologies and knowledge of SDLC including CI/CD, Application Resiliency, and Security
- Experience as a full-stack engineer in AWS cloud environments
- Requires depth of knowledge and experience in two of the following areas, with developing knowledge in the others.
- High-throughput, low-latency micro service development leveraging AWS services such EKS, ECS, Fargate, ELB, etc.
- High throughput near real time stream processing with services such Kinesis, Flink, ECS, EKS, etc.
- High volume feature engineering with services such EMR.
Preferred qualifications, capabilities, and skills
- Experience with recommendation and personalization systems