Senior Backend Engineer

Role Overview:

We are seeking an experienced Senior Backend Engineer for our innovation team to build the AI-native backbone of our platform. In this role, you will design and scale async production-grade backend systems that treat AI as a first-class citizen.

What You'll Do & How You'll Make Your Mark

• Design and scale async REST/WebSocket APIs in Python (FastAPI or similar), utilizing dependency injection, type hints, and clean vertical-slice architecture to support millions of small businesses.
• Implement multi-agent workflows using sequential, concurrent, and handoff patterns to route tasks among specialized LLM agents effectively.
• Create a provider-agnostic layer for integrating multiple LLM providers, enabling robust A/B testing and cost-aware routing strategies rather than relying on single vendors.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines optimized against vector stores such as pgvector, Chroma, or managed services.
• Design schemas and evolve data models using SQLAlchemy/SQLModel-style ORMs to support both traditional application logic and advanced AI-driven features.
• Instrument services with structured logs, distributed tracing, and cost/latency metrics, maintaining strict standards for p95 response times under production load.
• Take full ownership of end-to-end CI/CD pipelines, ensuring releases are boring, safe, linted, type-checked, tested, packaged, and deployed efficiently.
• Champion AI across the entire delivery lifecycle by setting guardrails for code generation review, provenance checking, licensing compliance, and defining boundaries for customer data in prompts.

Who You Are & What You'll Need to Succeed

• 5+ years of experience building production backend systems in Python with real async I/O expertise.
• Demonstrated hands-on experience designing and scaling REST or async APIs, including dependency injection and clean service architecture patterns.
• Practical experience integrating LLM APIs (OpenAI, Gemini, etc.) to build AI-readiness into backend systems from the ground up.
• Real-world experience with vector databases and RAG-style retrieval architectures beyond theoretical knowledge.
• Strong relational database skills encompassing schema design, query optimization, and disciplined migration practices.