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?

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.

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.

• 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.

• An engineering mindset that prioritizes long-term system stability and clean architecture over quick patches.
• The autonomy to drive technical decisions and responsibility for the outcome.
• A collaborative approach to problem-solving, welcoming direct feedback and technical debate.
• Curiosity about how AI tools fail in practice and a desire to build systems that gracefully handle those failures.
• A strong focus on the developer experience, understanding what makes an integration feel seamless or disruptive.

• Comprehensive experience in professional software development, demonstrating the technical maturity required for senior engineering problems.
• Strong programming skills in at least one modern backend language, with the readiness to work primarily in Kotlin.
• A deep practical understanding of concurrent and asynchronous programming, including coroutines, threads, async I/O, and synchronization primitives.
• A proven track record of building and shipping application workflows, third-party integrations, or service-backed logic.
• Hands-on experience working with AI-assisted development tools, alongside an understanding of task orchestration, tool usage, and prompt context management.
• A solid understanding of software engineering fundamentals, including data structures, debugging, observability, and test-driven development.
• Fluency in written and spoken English for day-to-day technical collaboration across distributed teams.

Success in this role means building robust, low-latency integration pipelines that make AI agents feel like a natural extension of the Air environment. You will earn the trust of the team by creating reliable, asynchronous workflows that handle unpredictable LLM behaviors without compromising IDE performance. You win when you move past inherited frameworks to establish internal standards for agent tooling, leaving the codebase cleaner, faster, and more maintainable than you found it.