Job responsibilities
Design and develop high-performance, latency-sensitive code, incorporate security requirements and reviewing code written by team members using software engineering best practices
Write secure, high-quality code and automated tests
Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by code
Identify opportunities to eliminate recurring issues to improve overall operational stability of software applications and systems
Participate in communities of practice across the group to drive awareness, consistency and adoption of modern technologies
Collaborate effectively as part of a global team
Provide out of hours application support and coordinate of Production releases
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Required qualifications, capabilities, and skills
Formal training or certification on Java concepts and proficient applied experience.
Understanding of Java 17+ fundamentals and frameworks (Spring Boot), OO programming paradigms, multi-threading, messaging technologies and computer networks
Experience with modern testing tools (JUnit, Mockito, Spring Test Framework)
Experience using and designing schemas/data structures in resilient SQL and NoSQL databases (e.g. CockroachDB)
Familiarity with maintaining and troubleshooting software running in a Linux environment, familiarity with the Linux operating system, system utilities, containers and cloud architectures and services
Strong interpersonal and communication skills, with experience working with globally distributed engineers and stakeholders
Understanding of the full software development lifecycle and agile approach
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
Preferred qualifications, capabilities, and skills
Hands on experience another statically compiled language like Rust, GoLang or C++
Experience in building high-performance, latency-sensitive Java applications
Experience with OSI Layer 7 proxies (e.g. Envoy)
Experience with gRPC and Google Protocol Buffers
Experience with infrastructure as code software, e.g. Terraform
Certified Kubernetes and public cloud knowledge (e.g. CKAD and AWS certifications)
