• Create architecture, prototypes, and design proposals that deliver near-term business value while aligning with the future-state product and platform vision. 

• Influence technical direction through architecture reviews, RFCs, design discussions, and hands-on collaboration. 

• Partner with senior developers, architects, and tech leads to define and execute the product/platform architecture roadmap. 

• Balance delivery speed, quality, maintainability, and long-term platform health when making technical decisions. 

• Break down large initiatives into parallelizable chunks of work that deliver incremental business value. 

• Champion proposals through all phases of the SDLC, from design through production implementation. 

• Contribute to improving the core product build, CI/CD pipelines, and overall SDLC. 

• Troubleshoot and eliminate root causes of persistent production issues; drive reliability, observability, monitoring, and incident response. 

• Keep technical documentation current and create new artifacts as needed. 

• Facilitate design discussions within and across teams. 

• Represent the team in technical discussions with Tech Leads, Operations, Product/UX, Security, Domain SMEs, and external stakeholders. 

• Act as a trusted technical leader, helping teams succeed through collaboration, influence, and shared ownership. 

• Mentor other developers through design reviews, joint agentic-AI sessions, and feedback on skills, prompts, and other agent inputs; contribute to raising overall engineering maturity. 

• Share knowledge of new technologies and industry best practices. 

• Evaluate emerging technologies, frameworks, and cloud capabilities that could benefit the platform. 

AI-Augmented Development 

• Use AI-assisted development tools — inline completion, conversational assistants, and agentic workflows — as a standard part of your daily workflow.  

• Critically evaluate and take ownership of all AI-generated output before it ships — verify correctness, security, and alignment with architecture and team standards.  

• Identify opportunities for agentic automation within your team, and lead the rollout of new AI-assisted workflows and tooling.  

• Mentor other developers on effective, responsible use of AI-assisted development tools.  

• Help establish team-level practices and guardrails for using AI tools safely and effectively.  

• Build and refine feedback loops that improve the team's collective use of AI tooling over time. 

Back-End Engineering Focus 

• Define and evolve the architecture of back-end services, establishing standards for scalability, security, and reliability. 

• Influence technical direction for back-end systems through design reviews, RFCs, and hands-on collaboration. 

• Partner with QA, Security, and Product to ensure robust, well-tested services. 

• Mentor back-end engineers and raise the bar on code quality and system design. 

• Degree in Computer Science, Software Engineering, or equivalent practical experience, with 8+ years of professional software development experience and demonstrated impact beyond a single team. 

• Deep expertise in Java, Spring Boot, distributed back-end systems, and cloud-native architecture at scale, ideally on AWS. 

• Experience designing and operating SaaS or multi-tenant platforms and owning the architecture of scalable back-end services. 

• Strong software fundamentals, including object-oriented programming, design patterns, SOLID principles, and a track record of advocating for code quality. 

• Experience with agentic-AI software development practices and responsible use of AI-assisted development tools. 

• Experience designing and consuming well-designed HTTP APIs, including REST, GraphQL, or similar approaches. 

• Experience mentoring developers and influencing architectural decisions across teams. 

• Strong written and verbal communication skills, with the ability to operate effectively in fast-moving environments with ambiguity and evolving requirements. 

• Strong initiative to improve processes, tools, methodologies, and product quality. 

Preferred Qualifications 

• Experience with cloud providers beyond AWS, such as Azure or Google Cloud. 

• Familiarity with containerization and orchestration technologies, including Docker and Kubernetes. 

• Contributions to open-source projects or a strong GitHub portfolio.