interface.ai is looking for a Staff Engineer for Nexus to build intelligent backend systems that will enable a new generation of productivity tools and decision-making copilots within financial institutions, improving operational efficiencies and driving revenue growth.
Requirements
- 8+ years of backend or platform engineering experience, with a deep understanding of distributed systems and API-driven architectures
- Experience building real-time data systems, enterprise workflow platforms, or backend infrastructure for intelligent interfaces
- Strong systems design skills—able to make architectural tradeoffs for scale, reliability, extensibility, and velocity
- Proficiency in building large, modular systems in languages such as Node.js, Go, Python, or similar
- Deep familiarity with identity systems, secure access control, and integration with external systems and APIs
- Track record of working across teams and domains to bring technically complex features to life
- Exposure to AI infrastructure, LLM orchestration, or intelligent assistants
Responsibilities
- Architect and build core backend services that power intelligent AI assistants and operational workflows for enterprise environments
- Design APIs and real-time data integration frameworks to support decision-making and task automation within secure systems
- Lead initiatives around search, routing, orchestration, and domain-specific reasoning—enabling fast, accurate, and contextual agent behavior
- Collaborate with infrastructure and AI teams to connect ML capabilities into repeatable, resilient system patterns
- Work on secure-by-default abstractions for identity, access, auditability, and error handling across distributed services
- Enable human-in-the-loop workflows by designing feedback mechanisms, confidence scoring, and intelligent fallback layers
- Drive adoption of scalable engineering practices across services: testing, observability, release safety, and performance tuning
Other
- Act as a technical lead and mentor across engineering, contributing to cross-functional architectural decision-making
- Experience in enterprise SaaS, compliance-heavy environments, or regulated data systems
- Understanding of structured knowledge systems, document stores, or semantic search
- Prior work building user-facing automation or internal tools that scaled across departments or clients
