Senior Software Engineer - Core Team

ZEDEDA•San Jose, CA

3d•$150,000 - $180,000•Hybrid

About The Position

We're looking for an experienced engineer to take ownership of complex, AI-powered systems built on a microservice and distributed architecture. A core part of this role is designing and developing AI agents that run natively in our infrastructure — agents that integrate deeply with our services, run reliably at scale, and deliver real value to customers. You'll ramp up quickly on existing codebases, ship enhancements, debug production issues across services, and shape architecture as the systems scale. This role is for someone who is comfortable navigating unfamiliar code, makes thoughtful trade-offs, and treats coding agents (Claude Code, Codex, Cursor, etc.) as a force multiplier in their daily workflow.

Requirements

5+ years of professional software engineering experience
Strong proficiency in Go (Golang) for production services
Solid experience designing and operating microservices and distributed systems at scale
Working knowledge of PostgreSQL, Redis, Kafka and Docker
Background in cloud infrastructure, Kubernetes, or edge computing
Track record of debugging hard problems in production distributed environments
Hands-on experience using coding agents (Claude Code, Codex, or similar) as part of your workflow — and a genuine interest in pushing what they can do
Clear written and verbal communication; works well asynchronously

Nice To Haves

Familiarity with Python and/or TypeScript/React
Experience with LLM-based systems, LangGraph, LangChain, or other agent frameworks
Exposure to MCP (Model Context Protocol) or LLM observability tools (Langfuse, LangSmith)
Open-source contributions

Responsibilities

Understand large, evolving codebases quickly and contribute meaningfully within weeks
Design, build, and operate services in a microservice and distributed systems environment
Diagnose and resolve production issues across services, databases, message queues, and LLM integrations
Drive architectural improvements — scalability, reliability, observability, and developer experience
Design and develop AI agents that run natively in our infrastructure — owning architecture, tool integration, reliability, and performance
Collaborate with other engineers and use AI coding agents effectively to accelerate delivery