Senior Software Engineer, Context Engine

Redis is a company that builds the product powering fast applications worldwide. They are seeking a Senior Engineer for the Context Engine team to develop core infrastructure for AI agents, ensuring speed and relevance while contributing to product direction.

Responsibilities:

• Build Context Infrastructure: Design and implement the systems that create, transform, and deliver context to AI agents—optimized for speed, relevance, and scale on top of Redis
• Ship Fast: Operate with startup-level velocity inside a well-resourced company. Prototype, test, and ship features in tight cycles. We value working software over long planning horizons
• Shape the Product: Contribute directly to product direction. You’ll work closely with leadership to define what we build, not just how we build it
• Write Great Go: Our Context Engine is built in Go. You’ll write clean, performant, production-grade code and set quality standards for the team
• Build with Agents: Use agentic coding tools and workflows daily. We expect you to be fluent in AI-assisted development and to push the boundaries of what’s possible
• Own Your Domain: Take full ownership of the systems you build—from design through production. High autonomy means high accountability

Requirements:

• 5+ years of experience in backend or infrastructure engineering, with a track record of shipping production systems
• Strong proficiency in Go
• Hands-on experience building AI agents or agentic systems—you understand how agents reason, plan, and use tools
• Fluency with agentic coding tools and AI-assisted development workflows
• Demonstrated high ownership and autonomy—you've thrived in environments where you set your own direction
• Strong opinions on the future of agents, context, and AI infrastructure—and the ability to back them up with working code
• Excellent communication skills—able to collaborate effectively across a distributed, global team
• Founder experience—you've started a company, built a product from scratch, or operated at the zero-to-one stage
• Experience with data infrastructure, streaming systems, or real-time data platforms (Kafka, Flink, Redis, or similar)
• Background in ML infrastructure, vector search, or retrieval-augmented generation (RAG) systems
• Contributions to open-source projects in the AI/ML or data infrastructure space
• Experience with cloud platforms (AWS, GCP, Azure) and modern deployment practices