● Own end-to-end architecture for core backend services, balancing scalability, reliability, security, and cost. ● Set technical standards, design patterns, and engineering best practices that other teams adopt. ● Lead architecture reviews and major design decisions, and evaluate emerging technologies for real business fit. Platform Development & Delivery ● Design and build highly available, distributed backend systems and the APIs that expose them. ● Stay hands-on with complex, business-critical implementation alongside the teams you influence. ● Guide teams through the full software development lifecycle, from design through production support. Engineering Excellence & Operations ● Champion quality, observability, and operational readiness across the services you help design. ● Lead root-cause analysis on complex production issues and drive fixes that improve long-term resilience. ● Raise the bar on code review, testing, and CI/CD practices across teams. AI-First Engineering ● Use AI coding agents (e.g., Claude Code, GitHub Copilot, Cursor) as a standard part of your workflow to accelerate development, refactor code, and debug production issues without sacrificing quality or security. ● Identify practical opportunities to embed AI-driven capabilities into the platform and into how the team builds software. ● Help establish responsible, secure norms for AI-assisted development across the org. Mentorship & Talent Development ● Mentor engineers at all levels through design reviews, pairing, and hands-on technical guidance. ● Influence technical direction across teams without relying on formal management authority. ● 8+ years of professional software engineering experience, including 3+ years in a lead or staff-level capacity. ● Proven experience owning architecture for a significant backend product area, ideally in a SaaS environment. ● Strong proficiency in a backend language (e.g., Java, C#, Kotlin) and experience with microservices, distributed systems, and API design. ● Experience with cloud platforms (AWS, Azure, or GCP), CI/CD pipelines, and container orchestration (Docker, Kubernetes). ● Hands-on use of AI coding agents to accelerate day-to-day development work. ● Demonstrated ability to influence technical direction and mentor engineers across teams. ● Bachelor's degree in Computer Science or a related field, or equivalent practical experience. ● Experience modernizing legacy platforms or leading large-scale technical migrations. ● Exposure to observability and SRE practices in a high-availability production environment. ● Experience with event-driven architectures and messaging systems (e.g., Kafka, RabbitMQ). ● Familiarity with AI/ML-enabled engineering workflows beyond coding assistance.