AI Productivity Engineer

Overview

As a Senior Software AI Engineer on Aircall’s Engineering Productivity (EngProd) team, you accelerate AI adoption across engineering by delivering practical, production-grade AI tooling and systems. You own end-to-end delivery, from discovery to measurement, and work with engineers to embed intelligence into daily workflows. The role emphasizes reducing friction, automating repetitive tasks, and driving real-world adoption and impact. You’ll shape how AI is applied responsibly to boost developer productivity and tool usage at scale.

Pay / Benefits

• Competitive salary package & benefits

Responsibilities

• Own rapid AI adoption across the engineering organization
• Identify high-friction engineering workflows where AI adds value
• Design and build production-grade AI-powered developer tooling (coding, testing, PR reviews, debugging)
• Create contextual, system-aware AI assistants using internal data and tooling
• Prototype and productionize AI-driven solutions with autonomy
• Automate workflows across GitLab, Jira, CI/CD, Slack, and observability tools
• Design and operate internal AI services and orchestration layers (e.g., MCP servers)
• Own solutions end-to-end: discovery, design, build, measure, iterate
• Collaborate with engineering teams to reduce friction and move tools into daily practice
• Measure adoption and impact through time saved and usage metrics

Key requirements

• 5+ years of software engineering experience with a recent focus on GenAI systems
• Experience building production-grade systems (not just prototypes)
• Hands-on experience with LLMs (OpenAI, Anthropic, etc.)
• Proficiency in prompting, retrieval, and context injection
• Experience with AI-powered tooling or internal platforms
• Solid backend engineering skills (APIs, services, integrations)
• Experience with developer tools (CI/CD, GitHub/GitLab, Jira, observability)
• Strong product mindset and ability to navigate ambiguous problems

• Collaborative mindset
• Strong product-focused thinking
• Ability to operate autonomously in ambiguity
• GenAI systems
• LLMs and prompting
• AI-powered tooling and internal platforms

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