At a Glance
- Tasks: Own and evolve technical infrastructure for cutting-edge biotech research.
- Company: AI-driven biotech platform revolutionising scientific discovery.
- Benefits: Flexible work environment, competitive salary, and opportunities for growth.
- Other info: Join a collaborative team pushing the boundaries of biotech innovation.
- Why this job: Lead the evolution of impactful tech solutions in a dynamic field.
- Qualifications: 5+ years in software engineering with expertise in cloud and data systems.
The predicted salary is between 70000 - 90000 £ per year.
You will own and evolve technical infrastructure across cloud operations, data systems, and product deployment. As a high-impact generalist, you will architect robust systems and migrate legacy infrastructure to AWS, directly enabling advanced discovery services. This role bridges the gap between internal ML research tools and production-ready APIs for external scientific users.
Why this role is remarkable:
- Full-stack ownership across backend services, frontend interfaces, and infrastructure automation without rigid corporate constraints.
- Lead the technical evolution of a core inference platform from an internal research tool to a production-ready external product.
- Design greenfield database architectures integrating complex scientific data sources to serve as the foundation for future discovery efforts.
What you will do:
- Manage and scale cloud infrastructure through Terraform across multi-account AWS organizations and automated CI/CD pipelines.
- Design and implement database systems to integrate structured biochemistry data with unstructured experimental data for ML training.
- Build and harden production APIs and React frontends to transition internal models into service-oriented products for external users.
The ideal candidate:
- 5+ years of software engineering experience with the ability to own complex distributed systems and data pipelines end-to-end.
- Proficiency in Python, Docker containerization, and at least one major cloud platform (AWS or GCP).
- High agency systems thinker comfortable working as a pragmatic generalist across infrastructure, backend, and developer tooling.
Required Skills:
- AWS
- Backend Development
- Frontend Development
- Machine Learning
- Python
- CI/CD
- Docker
- Distributed Systems
- Terraform
- React
- GCP
- Cloud Infrastructure
- Data Pipelines
- APIs
Required Languages: English
Staff Engineer at AI-driven biotech research platform employer: Jack & Jill
As a Staff Engineer at our AI-driven biotech research platform, you will thrive in a dynamic work culture that champions innovation and collaboration. With opportunities for full-stack ownership and the chance to lead the evolution of cutting-edge technology, you will be part of a team that values your expertise and encourages professional growth. Located in vibrant Cambridge or London, you will enjoy a stimulating environment that fosters creativity and offers unique advantages in the biotech sector.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Engineer at AI-driven biotech research platform
✨Tip Number 1
Network like a pro! Reach out to folks in the biotech and AI space on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving cloud infrastructure and data systems. This is your chance to shine beyond the written application.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and AWS skills. Practice coding challenges and system design questions to demonstrate your expertise in real-time.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Staff Engineer at AI-driven biotech research platform
Some tips for your application 🫡
Show Your Passion for Tech:When writing your application, let your enthusiasm for technology and innovation shine through. We love candidates who are genuinely excited about the role and can articulate why they want to be part of our AI-driven biotech research platform.
Tailor Your Experience:Make sure to highlight your relevant experience in software engineering, especially with cloud infrastructure and data systems. We want to see how your skills align with what we do, so don’t hesitate to draw direct connections between your past work and the responsibilities outlined in the job description.
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications. Avoid jargon unless it’s necessary, and make sure your key achievements stand out.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company and culture!
How to prepare for a job interview at Jack & Jill
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS, Python, and Docker. Brush up on your knowledge of Terraform and CI/CD pipelines, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex distributed systems or data pipelines. Think about challenges you've faced and how you approached them, as this role requires a high agency systems thinker.
✨Understand the Biotech Context
Familiarise yourself with the biotech industry and how AI is being integrated into research. Being able to speak intelligently about the intersection of technology and science will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions that demonstrate your interest in the role and the company. Inquire about their current projects, the team dynamics, or how they envision the evolution of their inference platform. This shows you're not just interested in the job, but also in contributing to their mission.
