About the Role

We're building a platform (architect.new) that lets anyone create, deploy, and manage autonomous AI agents with custom skills, tool integrations, and production-ready UIs. You'll work across backend, frontend, and infrastructure — reporting to the Product Architect.

What You'll Do

• Build and maintain the core agent orchestration engine, skill execution, and state management
• Develop the builder UI in Next.js for composing agents and workflows
• Implement real-time communication layers (WebSockets, SSE) for live agent interactions
• Own backend microservices in Python and Go
• Design and optimize MongoDB schemas for multi-tenant, high-throughput workloads
• Manage cloud infrastructure, deployments, and observability on AWS

Required Experience

Backend — Python & Go

• Building scalable microservices in Python (FastAPI) and Go
• WebSocket and SSE implementation; diagnosing socket-level issues
• MongoDB at scale — sharding, indexing, replica sets
• Authentication mechanisms — OAuth 2.0, JWT
• Pub/Sub patterns and event-driven architecture
• Queue management, state persistence, retry and dead-letter handling
• Understanding of latency, networking, and distributed systems performance

Frontend — Next.js

• CSR vs. SSR trade-offs and when to apply each
• Diagnosing hydration issues
• State management across client and server boundaries
• Scalable component architecture
• Deployment, reverse proxying, and build optimization

Infrastructure & Observability

• ECS management and CloudWatch log aggregation
• Cloud networking basics — VPCs, load balancers, security groups
• Managed services — DocumentDB, Redis
• SigNoz or similar observability tools

Version Control

• Git workflows — branching strategies, PR reviews, conflict resolution
• Repository management for microservice codebases

System Design

• LLD: Design patterns, SOLID principles, API contract design
• HLD: Distributed system architecture, service decomposition, scalability patterns, fault tolerance
• Database Design: Schema modeling (SQL & NoSQL), indexing, query optimization, consistency trade-offs

Nice to Have

• Experience with AI agent frameworks — tool use, skill orchestration, multi-step reasoning
• LLM integration patterns — prompt chaining, function calling, structured outputs
• Firecracker MicroVMs or E2B-style sandboxed execution environments
• Sandbox isolation, security boundaries, and secure code execution
• Agent memory and long-running task orchestration