Full Stack Software Engineer, GTM AI Automation
San Francisco OfficeFull-TimeMid-levelFull-stack
What You Will Do
- Build AI-powered tools and applications that accelerate Aircall's go-to-market efforts — from lead enrichment and workflow automation to intelligent dashboards and internal assistants.
- Work across the full product lifecycle: prototype, iterate, ship, and maintain production-grade solutions that GTM teams rely on daily.
- Embed with GTM stakeholders (Sales, Marketing, CS, Support, RevOps) to deeply understand their pain points, map workflows, and rapidly prototype solutions.
- Apply LLMs and AI APIs in novel ways to solve real-world GTM workflow problems — automating repetitive tasks, extracting insights from unstructured data, and enabling smarter decision-making.
- Create reusable code libraries, integrations, and MCP servers to enable consumption of AI-powered tooling across the GTM stack (Salesforce, Slack, Outreach, and more).
- Collaborate with the Data & Analytics team to pull customer usage, engagement, and pipeline data and leverage it within your tooling.
- Measure and iterate: deploy solutions, track adoption and impact against pre-defined metrics, and continuously refine based on end-user feedback.
- Write documentation and runbooks for productionized solutions so others can maintain and debug them.
What We Are Looking For
- 2–4 years of experience as a software engineer, data engineer, analytics engineer, product engineer, or ML engineer working on user-facing systems.
- Full-stack proficiency: comfortable building end-to-end applications with Python (FastAPI/Flask) on the backend and JavaScript/TypeScript (React) on the frontend.
- Hands-on AI/LLM experience is a must: you have built or prototyped LLM-powered workflows using APIs from OpenAI, Anthropic, or similar providers. You understand prompt engineering, model integration, and how to ship AI features into production.
- Familiarity with modern AI frameworks and patterns such as LangChain, LlamaIndex, or AutoGen, and architectures like RAG, vector databases, reranking, and agentic workflows.
- Strong product sense and ownership mentality: you take initiative, move quickly, and care deeply about whether your work is actually used and useful.
- Excellent communication skills: you're comfortable working directly with non-technical end users, gathering requirements, doing lightweight design, and presenting solutions.
- A builder's mindset with a bias toward action, experimentation, and shipping.
Nice to Have
- Prior experience in a GTM role (Sales Ops, Marketing Ops, RevOps, Sales, or Marketing) or significant experience building tools for GTM teams at a B2B SaaS company.
- Experience with the modern GTM tools ecosystem: Salesforce, Outreach, Clay, HubSpot, Slack APIs, Twilio, etc.Proven understanding of agentic AI systems, including designing, developing, and deploying AI Agents and MCP servers.
- AWS cloud experience — you've deployed and operated production applications on AWS and understand how to design for scalability and reliability.
- Former founder, or early engineer at a startup who built a product from 0 to 1.
- Curiosity about the rapidly evolving AI landscape: different models, paradigms, and tools being used in the wild.
