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Tiro Partners have been engaged by an exciting startup that has secured significant investment to scale its engineering team. You will build and ship core product features across the stack for AI voice agents serving trades businesses, shaping how the product works and how customers are engaged.
The role is onsite in Central London, paying £150-250K base plus equity. You will work in a backend-leaning full-stack capacity with Python or TypeScript, collaborating with customers to scope solutions
Tiro Partners have been engaged by an exciting start up who have received significant investment to scale the team with 4 staff level engineers. The company is building AI voice agents that help trades businesses run smoother, scale faster, and deliver better customer experiences.
This is a genuine ground up opportunity. You won't just be shipping code you'll be helping shape how the company works, how it engages customers and how it scales.
You will be building and shipping core product features across the stack which comprises of Python, TypeScript, cloud infrastructure, event-driven systems, and third-party integrations you will also be working directly with customers to understand their needs, scope solutions, and see them through to delivery.
The role is paying £150-250K on the base + Equity but for that you will be required onsite 5 days in Central London
5–10 years in full-stack software engineering (backend-leaning), with a strong AI product development background.
You have built and shipped AI products end-to-end real, hands-on experience with agentic systems.
You're a strong full-stack engineer in Python or TypeScript, with serious async Python, comfortable with async coroutines and handling errors properly in production async code
Experience at an early-stage startup (Series A or earlier) is highly deirable
Comfortable with modern cloud infrastructure, Kubernetes, serverless, distributed systems
Bonus points for voice AI, event-driven systems, or CRM integration experience, and a track record of working directly with customers.
This isn't going to suit people from large established companies or people with traditional ML/Data Science backgrounds unfortunately.