01Responsibilities
- 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.
- Design, develop, and maintain full stack solutions, including Java/Spring Boot backend services, RESTful microservices, and modern UI applications using React or Angular.
- Build secure, high-performing APIs and integrations; contribute to service reliability, resiliency, and performance tuning.
- Collaborate daily with Product, Design, and Data & Analytics to refine requirements, estimate work, and deliver iteratively using Agile practices.
- Write clean, maintainable code with strong unit/integration test coverage; participate in code reviews and design discussions.
- Support and improve CI/CD pipelines and engineering automation; champion best practices in quality and developer productivity.
- Contribute to production support: troubleshooting, incident triage, root-cause analysis, and preventative improvements.
- Participate in application, data, and infrastructure architecture conversations and help evolve platform standards.
Required Qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Hands-on software engineering experience delivering production applications, with a strong focus on backend and UI development.
- 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
- Proficiency with modern UI frameworks such as Angular or React (to effectively partner on end-to-end delivery).
- Proficiency in Java and Spring Boot, including building and operating REST APIs and microservices.
- Experience with modern Agile delivery practices (Scrum/Kanban), CI/CD, and DevOps-aligned development (automated quality gates, release pipelines). Experience with cloud and/or container platforms (e.g., AWS or Cloud Foundry, Docker/Kubernetes).
- Working experience with databases: Oracle and/or NoSQL datastores such as Cassandra or MongoDB (data modeling, query performance, reliability).
- Experience with observability tooling (metrics, logs, traces) and production readiness practices. Experience with UAT and/or accessibility testing.
- Strong Java 8 (lambdas/streams) + React/Angular full-stack development experience. Experience developing Kafka producers/consumers in Java
- NoSQL experience: Cassandra / DynamoDB / Elastic Search. Hands-on Cloud Foundry/AWS and building/maintaining CI/CD pipelines. Strong quality mindset (TDD, automation) and ability to lead design/code reviews and mentor engineers
Preferred qualifications, capabilities, and skills:
- Interest and ability to build agent-style tools/workflows that execute multi-step tasks using tools/APIs (e.g., orchestration, routing, workflow automation).
- Familiarity with reliability patterns for LLM applications, such as: Tool/function calling and structured outputs, Prompt iteration and evaluation & Grounding approaches such as RAG (retrieval-augmented generation)
- Awareness of responsible AI fundamentals: privacy-by-design, safe handling of sensitive data, and validating outputs for correctness and .
