Senior Software Developer (AI Agents & Integrations)

Are you a senior software developer who views LLMs not as a magic fix, but as components of a larger, complex system? Do you want to move past superficial prompt engineering to design deep, asynchronous workflows that make AI agents reliably useful for real-world developers and take ownership of technical decisions in a culture that treats engineering as a craft?

About JetBrains

We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale.

What you’ll do

AI coding agents are shifting how software is built, but making them truly effective within an IDE requires solving difficult orchestration and integration problems. Within the Air ADE Agents & Integrations team, our goal is to take existing agents – such as Claude Code, Gemini, and Junie – and integrate them deeply into the Air ecosystem across desktop, web, and cloud surfaces.

This is a backend-oriented engineering role where you will influence the core business logic that connects AI agent capabilities with everyday developer workflows. Rather than focusing solely on LLM training, you will solve problems around context management, tool orchestration, and error recovery. You will work closely with our core product engineers and specialized AI/ML teams to translate open-ended developer interactions into highly responsive, concurrent technical architectures. You will have full ownership over how these systems are built, directly impacting how millions of developers interact with AI tools.

Day to day, you will:

• Design, implement, and develop the core product and business logic for agent-based developer workflows in Air.
• Build deep integrations between Air product surfaces, external APIs, local CLIs, and AI coding agents.
• Improve the end-to-end user experience for agents, covering setup, context handling, task execution, and failure recovery.
• Write highly concurrent and asynchronous logic to manage multi-step agent interactions reliably.
• Use AI agents and assistants in your daily development work to analyze their limitations and improve our workflows from firsthand experience.
• Write clean, maintainable code, lead technical design discussions, and participate in peer code reviews.
• Partner with distributed product and ML engineering teams to break down complex architectural problems.

What you’ll bring