AI Productivity Engineer

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide. They are hiring an AI Productivity Engineer to accelerate AI adoption across the engineering organization by building AI-powered tools and systems that improve productivity and reduce friction in engineering workflows. Responsibilities: Take clear ownership of rapid AI adoption across the engineering organization; Identify high-friction areas in engineering workflows where AI can meaningfully improve productivity; Design and build practical, production-grade AI-powered developer tooling (coding, testing, PR reviews, debugging); Build contextual, system-aware AI assistants using internal data, codebases, and tooling; Explore, prototype, and productionize AI-driven solutions with strong autonomy on how problems are solved; Automate and streamline 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; Work hands-on with engineering teams to remove friction, enable usage, and move tools from delivery to daily practice; Measure success through adoption, impact, and tangible time saved for engineers Qualifications: 5+ years of experience as a software engineer, with recent focus on GenAI systems; Strong experience building production-grade systems, not just prototypes; Hands-on experience with: LLMs (OpenAI, Anthropic, etc.); Prompting, retrieval, and context injection; AI-powered tooling or internal platforms; Solid backend engineering skills (APIs, services, integrations); Experience working with developer tools (CI/CD, GitHub/GitLab, Jira, observability); Strong product mindset and comfort operating in ambiguous problem spaces Required Skills: Generative AI Systems, Large Language Models (LLMs), Prompt Engineering, Retrieval Techniques, Context Injection, AI-powered Developer Tooling, Backend Engineering, API Development, Service Integration, Developer Tools (CI/CD, GitHub/GitLab, Jira, Observability), AI System Orchestration, Model Orchestration, Security and Privacy in AI Systems, Product Mindset