AI Productivity Engineer - San Francisco or Bellevue
3 days ago
Seattle
Job DescriptionAircall 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, WhatsApp, 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. How We Work at Aircall: 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 (EngProd) 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.What You'll Do • 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 engineersWhat You Won't Do, • 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 productivityWhat We’re Looking For - Required Experience, • 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 spacesNice to Have, • Particularly interesting profiles are engineers who have built developer tools and are now evolving toward AI-native system design., • Prior experience building developer tools, internal platforms, or DevEx tooling, • Experience evolving traditional tooling into AI-assisted or AI-driven workflows, • Familiarity with MCP, agent-based systems, or model orchestration concepts, • Experience integrating AI with large codebases, monorepos, or complex CI/CD environments, • Exposure to security, privacy, and trust considerations in internal AI systemsHow You’ll Be Successful, • AI solutions you build are widely adopted and used regularly by engineers, • Engineering productivity measurably improves, using:, • existing metrics we already track (e.g. DevEx, CI, delivery, quality, flow), and/or, • new, clearly defined metrics you help introduce to capture AI impact, • Manual, repetitive workflows are reduced or eliminated, with clear before/after comparisons, • Engineering time is visibly saved and reinvested into higher-value work, • Improvements are demonstrated with data, not just qualitative feedback, • Adoption grows organically because tools are useful, fast, and well-integrated into existing workflowsTeam & Environment, • You’ll join the Engineering Productivity team, • You’ll work closely with engineers across the company, • Strong collaboration with Infrastructure and Security teams, • Product-oriented culture focused on outcomes, not hypeLocation, • United States (preferred: Seattle or San Francisco), • Open to strong US-based candidates in other locations