Founding Platform Engineer

Lyzr AI; Región Centro; Presencial; MXN 60.000 - 90.000; Jornada completa

Descripción de la vacante

A forward-thinking AI technology company is seeking a skilled developer to create, deploy, and manage autonomous AI agents. The role involves building scalable microservices in Python and Go, developing the user interface in Next.js, and managing cloud infrastructure on AWS. Ideal candidates will have a strong background in real-time communication layers, state management, and system design, with familiarity in observability tools. Join a dynamic team pushing the boundaries of AI technology.

Formación

• Experience with building backend microservices in Python and Go.
• Knowledge in implementing real-time communication layers.
• Familiarity with state persistence and event-driven architecture.

Responsabilidades

• Build and maintain the core agent orchestration engine.
• Develop the builder UI using Next.js.
• Manage cloud infrastructure and observability on AWS.

Conocimientos

Building scalable microservices in Python (FastAPI)

WebSocket and SSE implementation

Understanding of latency, networking, and distributed systems performance

State management across client and server boundaries

Herramientas

Git

AWS

MongoDB

Descripción del empleo

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

• Building scalable microservices in Python (FastAPI) and Go
• WebSocket and SSE implementation; diagnosing socket-level issues
• 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

• 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