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- Tasks: Join us as a Founding Engineer to build AI agents and develop full-stack ML applications.
- Company: Plexe is a Y Combinator-backed startup revolutionising the ML/AI lifecycle.
- Benefits: Enjoy high ownership, equity options, and a vibrant office in Canary Wharf.
- Why this job: Be part of a fast-paced environment where your ideas shape the future of AI technology.
- Qualifications: 3+ years in ML/AI systems, strong Python skills, and familiarity with web frameworks.
- Other info: Opportunity for relocation to our upcoming US office with visa sponsorship.
The predicted salary is between 43200 - 72000 £ per year.
Primary Location: London · Canary Wharf HQ (on-site). We plan to open a US office in the next ~6 months and will sponsor transfer visa for team members open to relocation.
Plexe is building AI agents that turn simple plain-English prompts into full production ML applications, including data pipelines, models, and more. We’re backed by Y Combinator (X25) and were named one of the spring batch's "Top-10 AI agent startups" by Business Insider.
We’re looking for a full-stack engineer with hands-on experience in building and deploying LLM-based products from scratch. You’ll develop multi-agent systems, build product front-end and backend APIs, and ultimately create AI agents that autonomously handle the entire ML development lifecycle.
Responsibilities
- Product Development: build distributed ML infra, multi-agent systems, observability, client-facing APIs, and more - eventually owning your own product or product lines.
- Technical Leadership: drive technical decisions and architecture design, helping shape the foundations of our platform.
- Cross-Functional Collaboration: work closely with co-founders to translate business vision and customer feedback into actionable engineering plans.
- Ownership: take full product ownership from ideation to launch, including integration into existing systems. Your roadmap is one quick chat away from reality.
Qualifications
We don’t have strict "formal" requirements - we just want to see you’re awesome and up for the challenge! That might look like this:
- Must-Have: 3+ yrs building ML/AI systems that served real users.
- Strong Python; comfort with AWS, Docker, Terraform/CDK, Postgres, etc.
- Experience with React, FastAPI, or other common web frameworks.
- An understanding of core concepts in ML, data science and MLOps.
- Nice-to-Have: Built agentic workflows / LLM tool-use.
- Experience with MLFlow, WandB, LangFuse, or other MLOps tools.
- Experience with AirFlow, Spark, Kafka or similar.
Why Plexe?
- Hard problems: we’re automating the entire ML/AI lifecycle from data engineering to insights.
- High ownership: first 5 engineers write the culture as well as the code. You have the power to fix whatever issue you can point at.
- Exciting environment: work at a fast-paced YC-backed startup with one foot in Silicon Valley.
Location and compensation: sweet office in central Canary Wharf; equity that can matter.
Founding Engineer (Full-Stack) employer: LinkedIn
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Engineer (Full-Stack)
✨Tip Number 1
Familiarise yourself with the latest trends in AI and ML, especially around LLMs. Being able to discuss recent advancements or projects you've worked on will show your passion and expertise during conversations.
✨Tip Number 2
Network with current employees or alumni from Y Combinator. They can provide insights into the company culture and what they value in a candidate, which can help you tailor your approach.
✨Tip Number 3
Prepare to demonstrate your technical skills through practical examples. Be ready to discuss specific projects where you've built and deployed ML systems, as hands-on experience is crucial for this role.
✨Tip Number 4
Showcase your ability to work cross-functionally. Think of examples where you've collaborated with non-technical teams to translate business needs into technical solutions, as this is key for the role at Plexe.
We think you need these skills to ace Founding Engineer (Full-Stack)
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications for the Founding Engineer position. Familiarise yourself with the technologies mentioned in the job description, such as Python, AWS, and React.
Tailor Your CV: Customise your CV to highlight relevant experience in building ML/AI systems. Emphasise your hands-on experience with the required technologies and any projects that demonstrate your ability to take ownership from ideation to launch.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of the challenges Plexe is tackling. Mention specific experiences that align with the role and express why you want to be part of a fast-paced startup environment.
Showcase Your Projects: If you have built any relevant projects or applications, include links to them in your application. This could be GitHub repositories or live demos that showcase your skills in developing ML applications and using the technologies listed in the job description.
How to prepare for a job interview at LinkedIn
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with building and deploying ML/AI systems. Highlight specific projects where you've used Python, AWS, Docker, or any relevant frameworks like React or FastAPI.
✨Demonstrate Ownership
Plexe values ownership, so share examples of how you've taken a product from ideation to launch. Discuss the challenges you faced and how you overcame them, showcasing your problem-solving skills.
✨Emphasise Collaboration
Since the role involves cross-functional collaboration, be ready to talk about your experiences working with co-founders or other teams. Illustrate how you translated business vision into actionable engineering plans.
✨Prepare for Technical Leadership Questions
Expect questions about technical decisions and architecture design. Think about how you've influenced technical direction in previous roles and be ready to discuss your thought process behind those decisions.
