About the role

Staff AI Developer shaping architecture and building systems for an AI grant research platform. Collaborating across Rails and Python systems with a focus on AI-enabled software development.

Responsibilities

Partner with Product to translate roadmap priorities into technical designs, implementation plans, and delivery strategies
Design and implement features across application, data, and infrastructure layers
Own and evolve core platform architecture across both Rails and Python systems
Make high-impact architectural decisions (service boundaries, modularization, data access patterns, scalability)
Build and optimize high-scale background processing systems (notifications, scoring, ingestion, exports, etc.)
Develop workflows spanning APIs, background jobs, ingestion pipelines, search/discovery, and reporting
Investigate production issues, identify root causes, and improve platform reliability
Implement AI-powered features including LLM orchestration, prompt workflows, and observability controls
Leverage AI-assisted development tools for coding, testing, refactoring, and documentation
Document architectural decisions and system behavior for long-term maintainability
Collaborate with Engineering, Product, Customer Success, and Support teams to continuously improve the platform

Proven experience as a Senior or Staff-level engineer building production SaaS or data platforms
Deep expertise in Ruby on Rails, including performance, architecture, and long-lived systems
Strong hands-on experience with Python (FastAPI or similar frameworks preferred)
Experience across both application platforms and data systems (APIs, ingestion, pipelines, reporting)
Strong background in background processing systems (e.g., Sidekiq, Redis, queues, schedulers)
Solid understanding of PostgreSQL schema design and performance optimization
Experience designing and operating production APIs (REST, auth, versioning, validation)
Comfort working in cloud-native, containerized environments
Experience with search and discovery systems (full-text, semantic, vector search)
A demonstrated AI-first development approach, using LLMs and automation tools
Strong understanding of security best practices (auth, data isolation, secrets management)
Experience with CI/CD pipelines, testing frameworks, and code quality tooling
Excellent communication skills, especially around technical decision-making.