Fullstack Engineer

We’re looking for a full‑stack engineer who blends strong Java fundamentals with a modern view of how AI is reshaping software delivery. This role sits at the intersection of backend engineering, cloud-native development, and hands‑on AI‑assisted coding practices. You’ll help evolve our engineering workflows, guide the team on responsible and effective use of AI tools, and contribute across the stack where needed.

We’re open to global talent and will move quickly wherever we can staff the role soonest. What You’ll Work On Build and enhance backend services and APIs using Java and Spring Boot within a microservices architecture Develop and maintain CI/CD pipelines, infrastructure automation, and containerized workloads running on AWS (ECS, Lambda, CloudFormation, or comparable tooling) Contribute to front‑end development when needed, especially React‑based internal dashboards and tools Implement performant, thread‑safe solutions using Java concurrency patterns and best practices Act as the team’s AI‑SDLC practitioner—establishing workflows, guardrails, and coding standards for AI‑assisted development Share practical insights from real‑world use of AI coding assistants (Copilot, Claude, Cursor, etc.)—where they shine, where they fail, and how to structure prompts, skill files, and integrations for reliable output Support the team’s adoption of Microsoft Foundry and contribute to emerging integration patterns Help shape a culture of experimentation, continuous improvement, and thoughtful engineering Required Experience 5+ years of professional Java engineering experience, including strong command of multithreading, concurrency, and core design patterns Hands‑on Spring Boot experience building APIs and microservices Practical experience working in a DevOps delivery model on AWS—CI/CD, containers, infrastructure automation Demonstrated use of AI coding assistants in real delivery work, with informed opinions on effective workflows and common pitfalls Understanding of AI‑augmented SDLC practices: prompt engineering for code generation, managing skill/knowledge files, AI‑assisted code review, test generation, and documentation automation Familiarity with concepts such as MCP integrations and IDE‑level AI tooling configuration Preferred Experience Exposure to Microsoft Foundry or Azure AI services Understanding of asset management concepts (portfolios, benchmarks, performance data, instrument types)—helpful but not required Experience with event‑driven or message‑based architectures Python familiarity for scripting or pipeline support What We Value Engineers who have experimented deeply with AI tools—who’ve broken things, learned from it, and can help others avoid the same traps Strong engineering fundamentals paired with curiosity about how AI is changing how we design, test, and ship software Clear communicators who can translate AI tooling decisions into practical team guidance A builder’s mindset—ownership, initiative, and a bias toward shipping #J-18808-Ljbffr