Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by code.
Drives architectural reviews, code reviews and business demos.
Assesses compliance, risks, and vulnerabilities to ensure all systems and baselines are operationally sound, performant at scale, and exceed customer expectations.
Contributes to the on-going development of the team, including recruitment, paired programming, peer review and mentoring.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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 software engineering concepts and 5+ years applied experience.
Excellent understanding of Java 17+ fundamentals and frameworks (e.g. Spring Boot), OO programming paradigms, multi threading, messaging technologies, and computer networks. Experience of low-latency programming techniques and technologies (e.g. Inter-Process Communication, Memory-Mapped Files and Ring Buffers).
Experience with gRPC and Google Protocol Buffers. Experience of working on distributed systems and detailed knowledge of distributed systems design patterns.
Detailed knowledge of relational database technologies (e.g., PostgreSQL and CockroachDB), database resiliency, recoverability, scalability, and security.
Experience with event-driven architecture and distributed messaging technologies (Kafka). Experience with diagramming software (e.g., Lucid, Draw.io, Visio) and technical writing.
Passion for technical innovation and staying up to date with emerging technologies.
Understanding of the full software development lifecycle and agile methodologies.
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Preferred qualifications, capabilities, and skills
Hands on experience another statically compiled language like Golang, Rust or C++.
Experience with caching technologies, e.g. Apache Ignite, GridGain, Hazelcast or Redis.
Experience with infrastructure as code software, e.g. Terraform
