AI Productivity Engineer - San Francisco or Bellevue

Aircall is a unicorn AI‑powered customer communications platform used by 22,000+ companies worldwide to drive revenue, faster resolutions, and scale. We’re redefining what a customer communications platform can be—by combining voice, SMS, Whats App, and AI into one seamless workspace.

Our momentum comes from a simple but powerful idea: help every customer‑facing team work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post‑call tasks, and AI Assist Pro delivers real‑time guidance that helps people do their best work. The result—companies grow revenue, deliver faster resolutions, and scale service.

We’ve built a product customers love and a business that scales fast. Aircall operates in nine global offices (Paris, New York, San Francisco, Sydney, Madrid, London, Berlin, Seattle, and Mexico City), and is backed by world‑class investors. Our teams are shipping AI innovation faster than ever and expanding across new product lines and markets.

At Aircall, you’ll join a company in motion—ambitious, profitable, and product‑driven—where impact is visible, decisions are fast, and growth is real.

At Aircall, we believe in customer obsession, continuous learning, and delivering extraordinary outcomes. We value open collaboration, taking ownership, and making smart, informed decisions with speed and precision. If you thrive in a fast‑paced, team‑driven environment where curiosity, trust, and impact matter, you'll fit right in.

We are hiring a Software AI Engineer to join the Engineering Productivity (Eng Prod) team at Aircall.

Your mission is to accelerate AI adoption across the engineering organization by building AI‑powered tools and systems that measurably improve how engineers work—reducing friction, automating repetitive tasks, and embedding intelligence directly into everyday workflows.

This is not a research role and not a customer‑facing product AI role
.

You will build practical, production‑grade AI solutions that engineers use daily, and you will be accountable for their real‑world adoption and impact.

This role is about using AI to make engineers more effective
, not about chasing trends.

If you enjoy building real systems that people rely on every day — this role is for you.

• 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 product ionize AI‑driven solutions with strong autonomy on how problems are solved
• Automate and streamline workflows across Git Lab, 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

• Build AI features for customer‑facing products
• Work on speculative AI research without clear outcomes
• Act as a general internal support team
• Own generic ML infrastructure unrelated to developer productivity

• 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, Git Hub/Git Lab, Jira, observability)
• Strong product mindset and comfort operating in ambiguous problem spaces

• Particularly interesting profiles are engineers who have built developer tools and are now evolving toward AI‑native system design
  .
• Prior experience building developer…