Applied AI Engineer (Staff Level)
Elyos AI · London ·
- Work mode
- Onsite
- Seniority
- Staff
- Category
- AI engineering
- Company size
- 11-50
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Elyos AI is seeking an Applied AI Engineer to build and scale AI voice agents for customer service. You will work across the full stack, designing LLM-based workflows and voice pipelines while collaborating directly with customers to deliver production-ready solutions.
About Elyos AI
We’re building the next generation of customer service with AI Agents. Our agents answer calls, reply to emails and WhatsApp messages, make bookings, take payments, and operate the CRM in the same way a human would.
We founded Elyos in June 2023 and took part in the Y Combinator S23 batch. Our founders spent four months in San Francisco living and breathing AI. Since then, we’ve been growing revenue ~30% month on month and shipping fast. It’s been wild so far - and we’re just getting started. We recently raised a $13m series A to turbocharge our growth.
At Elyos, we’re building AI voice agents that help trades businesses run smoother, scale faster, and deliver better customer experiences. As one of our founding engineers, you won’t just build software - you’ll shape the way Elyos works, interacts with customers, and grows. If you love building things from the ground up, solving complex technical challenges, and working with cutting-edge AI tech, you’re in the right place.
Build and ship core product features across our stack (Python, TypeScript, cloud infra, event-driven systems, third party integrations).
Design, build, and iterate on AI voice agents - prompt engineering, tool calling, conversation design, and orchestration across speech-to-text, LLM, and text-to-speech pipelines.
Make our agents measurably better: build evals, monitoring, and feedback loops so we know how agents perform in the real world, catch regressions, and turn live customer conversations into improvements.
Own the lifecycle: work directly with customers to understand their needs, scope solutions, and deliver outcomes.
Move fast, when it matters: know when to hack an MVP to deliver value quickly, and when to invest in scalable foundations.
Raise the bar: use best practices everywhere (e.g. testing, documentation, reliability, security) and help others do the same.
Customer-obsessed: You start with the customer. You empathise with their needs, ask the right questions, and build with their success in mind.
Biased for action: You try stuff. You move quickly, experiment often, and aren't afraid to learn in public.
Owner's mindset: You don't wait for permission - you take responsibility for outcomes and raise the bar for the whole team.
Ambitious & bold: You think big and take bets. You're excited to explore new ideas, technologies, and markets that others might shy away from.
Team-first collaborator: You make the next pot of coffee. No task is beneath you, and you care about building a team where everyone can thrive.
Care deeply: You give a shit about the quality of your work. If something you built isn't great, it nags at you until you make it better.
Strong fundamentals in software engineering - you can design, debug, and ship reliable systems.
Proficiency with at least one of our core languages (Python or TypeScript) - or proof that you can learn what's needed.
Hands-on experience building with LLMs in production - prompting, tool calling, RAG, or agentic workflows - and shipping AI products end-to-end (at a startup, on a side project, in open source, or at scale in a larger company).
An eye for the non-deterministic: you understand that AI systems fail in weird ways, and you know how to test, evaluate, and harden them for real users.
Comfort working across the stack - frontend, backend, infrastructure. You are everywhere.
Ability to work directly with customers or non-technical stakeholders to scope, negotiate, and deliver solutions.
A track record that shows drive: maybe you've launched something on your own, contributed to open source, or taken ownership of hairy projects others avoided.
Experience with voice AI - speech-to-text, text-to-speech, telephony, or real-time audio - and the latency and reliability challenges that come with it.
Familiarity with LLM evals, observability, or fine-tuning workflows.
Early-stage startup experience, especially in AI, voice platforms, or event-driven systems.
Familiarity with modern cloud infrastructure (Kubernetes, serverless, distributed systems).
Evidence of customer empathy - support experience, founder experience, or just building things that solved real user pain.
💸 Competitive salary & equity - we are building together, we win together
📚 AI-focused learning & development - stay ahead of the curve.
✈️ Team socials & annual offsites - cool destinations included(last year we went to Greece!).
🏥 Private healthcare - because your well-being matters.