Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.
As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations.
Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow.
About The Role
- You will work end-to-end, contributing to our new Agentic AI Agents, and managing the safe release of your features to our customer base. This is a two-way communication within Synthesia using conversational AI technology.
- Your work will be a combination of UXD, infrastructure, and machine learning challenges. You will contribute across infrastructure code, prompt engineering and working directly with LLMs.
- You will have sole ownership of projects that span months, requiring you to have the ability to break a problem down into small steps that can be delivered and validated iteratively.
- You will work directly with the product manager responsible for your project, meaning that you will be expected to ideate and focus on the commercial problem that you're solving, and you will have the opportunity to shape the direction of the product.
- You will evaluate your own work, leveraging our data pipeline and frameworks that we have established to understand the impact your features have on our commercial objectives and pivoting where necessary.
- You will consider the long-term direction of the team, making sure that we are developing the engineering capabilities that will allow us to stay ahead of the challenges we are likely to encounter in 6-12 months' time.
- At least seven (7) years of experience as a software engineer, at least 3 on the senior/lead level.
- You have experience in a high-performing engineering team that is operating at scale. This could come from a scale-up environment or a more established organisation recognised for building and shipping with a great engineering culture.
- An ability to work across the stack, with deep knowledge on server side, Machine Learning and all things back end related. BE only experience is OK if you are happy to occasionally help out with FE.
- Relevant engineering experience for a team building an enterprise-grade SaaS product delivering AI-powered video generation; billing systems, experimentation platforms, video delivery systems, online editors, real-time collaboration and so on.
- Strong alignment with commercial success.
- Previous leadership experience of smaller teams is a plus.
We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why,
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