About the Role

We are hiring a SeniorSoftware 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.

What You’ll Do

As a Software AI Engineer, you will:

• 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

What 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 productivity

What 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 spaces

Nice 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 systems

How You’ll Be Successful

You’ll be successful if:

• 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 workflows

Team & 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 hype

Location

• London

• Collaboration with teams in Europe/US expected

Why Join Aircall

• High-leverage role with company-wide impact

• Direct influence on how hundreds of engineers work every day

• Strong leadership support and clear mandate

• Opportunity to shape how AI is applied responsibly and pragmatically

Bottom Line

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.