Senior Software Engineer, Applied AI

Aircall•Seattle Office, WA

8h•$181,000 - $220,000

About The Position

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We’re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace. Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence. Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We’ve built a product customers love and a business that’s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines. At Aircall, you’ll join a company in motion. We’re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth. How we work at Aircall: We’re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you’ll feel at home here. We are looking for a Senior Software Engineer to help build agentic systems that would automate workflows for different internal functional departments at Aircall. This role combines deep software engineering skills with a desire to understand and automate workflows of stakeholders across Marketing, Sales, Customer Support, Customer Success, Finance, HR, Legal, Engineering, Product and many other functional areas using AI agents. Ideal candidates bring curiosity, a love for solving ambiguous problems, and hands-on experience applying LLMs in production.

Requirements

6+ years of software engineering experience, with at least 2 years working directly on AI/ML-powered applications.
Strong fluency in AI tooling (e.g. OpenAI APIs, Anthropic APIs).
Strong proficiency with modern backend languages (Python, Go, or similar)
Practical understanding of LLMs, prompt engineering and agentic architectures.
High degree of ownership and comfort in experimental, fast-moving environments.
Ability to take complete ownership of AI solutioning end-to-end starting from gathering requirements from stakeholders to deploying solutions in production.

Nice To Haves

Exposure to customer-facing roles or user research for AI product development.
Familiarity with retrieval techniques (e.g., vector databases, RAG).
Excellent problem-solving, communication, and teamwork skills, with the ability to explain complex AI concepts to non-technical stakeholders.
Bachelor’s Degree in Computer Science, Engineering, or a related field

Responsibilities

Partner with internal stakeholders to understand their daily workflows to surface and document those that can be automated with AI.
Build autonomous and semi-autonomous agent workflows that interact with browsers, codebases, and APIs to complete complex content operations.
Learn and contribute to prompt engineering strategies, with guidance on building agentic workflows, memory systems, and multi-step reasoning.
Build and operate MCP Servers that can be called by AI Agents.
Design and build proprietary agent libraries, prompting strategies and benchmarking frameworks.
Build and operationalize AI solutions with retrieval techniques (e.g., RAG, vector DBs) for context-aware applications.
Prototype, test, and optimize AI-powered applications, including retrieval-augmented generation, workflow automation, and agentic experiences.
Collaborate with cross-functional teams to align AI features with user needs and business goals, gaining exposure to product and platform thinking.
Stay current on advancements in AI technologies, frameworks, and best practices, and evangelize AI capabilities internally and externally.
Provide technical support, documentation, and training to facilitate adoption and effective use of AI solutions.
Participate in technical discussions, architecture reviews, and sprint planning.
Contribute to knowledge sharing and technical documentation.