• Lead the design and implementation of backend services and APIs for key product areas, balancing delivery speed with reliability, scalability, and maintainability. • Partner with Product and Design to clarify requirements, propose solutions, estimate effort, and deliver milestones with clear success metrics. • Build and operate applied AI features in production (e.g., LLM-backed workflows, evaluation/guardrails, retrieval patterns, experimentation, and monitoring) with a focus on quality, safety, and cost. • Contribute to architecture decisions through RFCs/design docs, proposing pragmatic patterns for service boundaries, data models, async workflows, caching, and migrations. • Write high-quality code and raise the bar through code reviews, pairing, and sharing best practices; mentor junior engineers as needed. • Improve operational health for the systems you own: observability, performance tuning, reliability improvements, and on-call outcomes. • Participate in an on-call rotation and help debug/resolve production issues; contribute to post-incident learnings and follow-ups. • Break down product requirements into well-scoped tickets and workstreams, coordinating with teammates to deliver predictably.

• Contribute hands-on to the codebase, solving complex problems and building high-quality software with Java (Spring, Spring Boot) • Participating in technical decision-making and architecture design in modern cloud environments (GCP, Terraform, CI/CD, observability tools) • Champion agile ways of working, encouraging openness, knowledge sharing, and continuous improvement • Work with a DevOps mindset in a security-conscious environment

• Architect Core Systems: Develop scalable components of a multi-agent system using FastAPI, Django, and pydantic-ai • Design Robust Data Models: Define and optimize domain models and PostgreSQL schemas for high-performance enterprise applications • Own Technical Decisions: Make pragmatic framework, tooling, and scalability choices from design through production • Write Clear, Maintainable Code: Build systems the whole team understands and can extend confidently • Integrate AI Thoughtfully: Connect AI agents into seamless user experiences without over engineering

• Own Cloud Platform : Design and implement scalable backend services on AWS for the GNXT cloud backbone • Define Data Architecture : Create and maintain canonical data models across business units and integration points • Establish Architectural Standards : Define guardrails and best practices for platform evolution and system design • Build Secure APIs : Develop REST APIs for cross-product integration with robust security and performance • Implement Access Control : Design identity management, multi-tenancy, and access control systems • Support System Integration : Enable integration of measurement systems into the customer platform • Infrastructure Design : Contribute to cloud infrastructure architecture and deployment strategies • Ensure Quality : Maintain clean architecture principles with focus on security, scalability, and maintainability • Mentor and Review : Guide other engineers through code reviews and technical mentorship