We’re two commercial and operational co-founders with a proven track record in growing and scaling companies—including a $43M trade sale.  Between us, we’ve led M&A deals, built high-performing teams, and launched multiple startups. After collaborating closely for the past six months, we’ve decided to build something much bigger together. 

Now, we're assembling a world-class founding team to bring our vision to life.

We're building the next billion-dollar lean startup, and we’re looking for a forward-thinking technical founding engineer to join us. You’ll be the technical brain behind the product, owning architecture and execution while shaping the future of the business from day one.

We're now looking to bolster this great founding team with a forward-thinking technical engineer who shares our enthusiasm and brings equally excellent technical finesse. To put it bluntly: if you build something great, we’ll sell the sh!t out of it, and we'll have fun doing it! 🚀

Join us as the Founding Lead AI Engineer, where you’ll architect and build the agentic core of our next-gen SaaS platform. This isn’t just about integrating LLMs, it’s about engineering AI-native systems from the ground up: dynamic agents, retrieval-augmented workflows, vector-based memory, and continuous learning loops.

You’ll lead the development of our foundational AI layer—working with tools like RAG pipelines, vector databases, prompt orchestration frameworks, and custom LLM integrations (built primarily on Azure). From prototype to scale, you’ll shape not just our tech stack, but how AI thinks, acts, and executes within our product.

This is a rare opportunity to:

• Build real AI systems—not wrappers—with agency, memory, and autonomy
• Own the technical direction of a category-defining product
• Work alongside experienced, go-to-market obsessed founders who know how to scale

• Design intelligent agent frameworks and retrieval pipelines that enable dynamic, real-world decision making.
• Architect modular, testable AI systems that integrate seamlessly with our core backend and product layer.
• Create flexible APIs that power decision automation and context-aware execution.

• Deploy and fine-tune open or closed-source LLMs to serve dynamic, context-rich use cases.
• Implement embedding models and search workflows to provide grounding, relevance, and long-term memory.
• Continuously optimize model performance and pipeline speed, balancing quality and cost.

• Structure ingestion pipelines for both structured and unstructured data.
• Build foundational components that allow our AI systems to learn from real-world signals and interactions.
• Enable real-time, feedback-driven improvement across key AI workflows.

• Partner closely with the commercial founders to define the AI roadmap and product priorities.
• Work alongside full-stack engineers to integrate agentic capabilities into the end-user experience.
• Lead with a lean, iterative mindset, automate what can be automated, and always ship value.
• Stay sharp on LLM innovation, agentic tooling, RAG systems, and co-pilot frameworks.

• ✔️ A seasoned AI/ML engineer with 2+ years of hands-on experience in deploying LLMs, RAG pipelines, and AI search technologies. (We want operators with real experience not just PHD’s)...
• ✔️ You’ve worked with LLMs, search pipelines, or agents—and know the difference between demo and scale.
• ✔️ You think in systems and flows, not just model performance.
• ✔️ Experienced with vector search technologies.
• ✔️ Deeply curious, execution obsessed, and allergic to fluff.

Requirements

• 2+ years of hands-on experience in deploying AI/ML systems in production
• Fluent or Native English (written and spoken) is essential.
• Proven experience building with large language models (LLMs), retrieval-augmented generation (RAG), or vector search technologies.
• Deep knowledge of machine learning engineering, prompt orchestration, and model optimisation.
• Experience architecting AI workflows involving embeddings, memory, reasoning, and automation.
• Familiarity with AI pipeline tools, versioning, and production-ready deployment practices.
• Strong programming skills in Python and experience working with API-first backends.
• Ability to design and integrate AI systems into broader product infrastructure.
• Comfort working in high-ownership, low-structure startup environments.
• Bonus: Experience with agentic frameworks, LangChain, Semantic Kernel, or co-pilot development.

Benefits

• Excellent early-stage equity — up to 10.0%.
• Competitive salary post-funding, aligned with market and contribution.
• True founding role — shape the product, company, and technical culture from day one.
• Work with proven commercial and operational operators — our founding team includes experienced founders with a $43M exit, deep GTM expertise, and a track record of scaling companies.
• Be part of something meaningful — we’re building an AI-first SaaS company tackling real, valuable problems with real-world impact.
• Remote-first work culture — work from anywhere in the world 🌍
• Timezone alignment — must be available to collaborate across UTC±2 (e.g., UK, Europe, Africa).
• Flexible hours — async-friendly, outcome-focused team.
• Zero bureaucracy, high trust — full autonomy and ownership from the start.
• Ground-floor opportunity — your decisions, code, and thinking will shape the product, the stack, and the company.

⚠️ Please note: this is an equity-first founding role until we raise funding. If you’re not comfortable with this structure, we totally understand—but this likely won’t be the right fit.
We’re looking for someone who sees this not just as a job, but as a chance to build something category-defining alongside a team who’ll go all-in with you.

🚀 At Launchyfi, we create the perfect match between your GTM and the tools that drive unstoppable growth — so you can focus on closing deals, not managing chaos.
→ Ex-SaaS founders and operators who know how to scale.
→ End-to-end GTM execution that fuels growth and revenue.
🌍 Ready to scale? Let’s go.