Senior Full Stack AI Engineer

We help companies change their culture, and we sell straight to CEOs rather than HR. We’ve been profitable for 8 years, we have users in more than 50 countries, and we’re growing inside one of the world’s top CEO networks. So you’d be joining a business with real clients and real revenue.

Our stack is Ruby on Rails, React/TypeScript, Flutter and Google Cloud.

We want a small team that gets a lot done by working with AI agents. In practice, that means you’d spend less time typing out code by hand and more time setting up agents, automating the boring stuff and building tools that help us ship faster.

We’re after someone who’s in it for the long haul. If you like spotting what needs doing and just getting on with it, and you’d rather own the result than wait for a ticket, you’ll probably enjoy working with us.

🔧 What you’ll do

Build products end-to-end

• Own features from discovery and problem definition through deployment and iteration
• Work directly with stakeholders and users to turn ambiguous requirements into effective solutions
• Build intuitive frontends, robust backend services, APIs and integrations
• Make pragmatic trade-offs between UX, speed, simplicity, scalability and quality
• Use feedback and product metrics to measure real value

Build and work with AI agents

• Use autonomous coding agents and AI dev tools as a core part of your daily workflow
• Design and build AI agents integrated with Slack, so users can trigger workflows, request changes and complete tasks in natural language
• Develop Model Context Protocol (MCP) servers connecting agents to internal systems, APIs, databases and external services
• Build and extend CLIs that make apps, infrastructure and workflows accessible to engineers and agents
• Implement agent workflows using tool calling, structured outputs, context management and orchestration
• Create automation that lets agents run tests, manage pull requests and validate their own work
• Experiment with emerging AI capabilities and apply them to real problems

Own quality and delivery

• Design, test and deploy production-grade software across the stack
• Review and validate AI-generated code for security, reliability, performance and maintainability
• Build automated tests, evaluation frameworks and feedback loops for both product and agent performance
• Improve developer experience, CI/CD, deployment workflows and observability
• Own the full lifecycle of what you build

✅ Must have

• Strong full-stack experience: modern frontend, backend, APIs and relational databases
• Experience building and maintaining production web apps (Rails is valuable; comparable frameworks equally welcome)
• A strong product mindset: you understand user problems, challenge requirements and prioritise business impact over technical complexity
• Hands-on use of AI coding tools (Claude Code, Codex, Cursor or similar) in real workflows
• Experience with API integrations, automation, developer tools or CLIs
• Familiarity with LLM APIs, tool calling and agent-based patterns
• Understanding of MCP and how agents interact with external tools
• Experience with automated testing, Git, CI/CD and production deployments
• Ability to take an ambiguous problem from idea to working product independently
• Excellent problem-solving, engineering judgment and communication

➕ Nice to have

• Slack bots, Slack apps or conversational agent interfaces
• Designing MCP servers and custom agent tools
• Orchestrating multiple AI agents or autonomous development workflows
• Ruby on Rails, Hotwire, React, TypeScript or Python
• Agent frameworks such as OpenClaw or LangGraph
• RAG, embeddings, vector databases and LLM evaluation
• Docker, cloud infrastructure, ephemeral environments and automated deployments
• Internal developer platforms or workflow automation systems
• Small, fast-moving product teams or early-stage startups

How we think about engineering As AI gets better at implementing software, the highest-value skills are shifting toward understanding problems, designing systems, directing agents and validating outcomes. We value engineers who:

• Think in outcomes, not tickets
• Have strong product intuition and question whether a feature should exist at all
• Are AI-native and treat agents as collaborators
• Build tools for agents, not only humans
• Automate repetitive work
• Prefer the simplest effective solution
• Ship, learn and iterate
• Take ownership from idea to production
• Experiment and challenge conventions

🎯 What success looks like in your first few months

• Independently shipping valuable features across our applications
• Building and improving AI agents that work with users through Slack and other interfaces
• Creating MCP integrations and CLI tools that let agents operate our systems
• Using AI coding agents to speed up implementation, testing and delivery
• Spotting opportunities to automate engineering and operational workflows
• Making sound product and technical decisions with minimal supervision
• Helping a small team deliver the impact of a much larger one

🌟 Why join us

• Work in an AI-native, product-driven environment where agents are central to how we build real-world work on agent systems, MCP integrations, automation and intelligent products
• Meaningful ownership of product direction and technical decisions
• Freedom to experiment and turn successful experiments into production capabilities
• High autonomy, fast decisions, minimal bureaucracy
• A chance to help define modern software engineering in an AI-first organisation

Our philosophy: great engineers don’t just write software. They understand problems, build the right solutions and create the tools and intelligent systems that make delivering value faster, simpler and more scalable.

How to apply

Resume + cover letter + a 3-minute video on why you're the right fit → aghadimi@forumsatwork.com, cc rtenyo@forumsatwork.com and sbashiru@forumsatwork.com

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