At a Glance
- Tasks: Design and build AI-native systems for enterprise data management and security.
- Company: Early-stage tech company focused on AI, cyber security, and data platforms.
- Benefits: Competitive salary, equity options, private medical insurance, and hybrid working.
- Other info: Opportunity for significant influence on product direction and architecture.
- Why this job: Join a small, dynamic team and shape the future of AI-driven enterprise solutions.
- Qualifications: Experience in software or AI engineering, strong Python skills, and a collaborative mindset.
The predicted salary is between 80000 - 100000 £ per year.
Location: London (Hybrid – 2–3 days on-site, flexible)
Salary: Competitive DOE + Bonus + Equity
Company Overview
We are working with an early-stage technology company building AI-native systems that help large organisations better understand, govern, and secure complex data and identity ecosystems. Operating at the intersection of AI, cyber security, and enterprise data platforms, the business is focused on transforming how organisations model access, risk, and data relationships across increasingly distributed cloud environments. The team is small, highly technical, and product-focused, with a strong bias toward ownership, rapid iteration, and building systems that operate in complex, real-world enterprise environments. Engineering sits at the centre of everything, and individuals are expected to have a direct impact on product direction and architecture.
The Role
We are seeking a Founding AI Engineer / Engineering Lead to join the business at a pivotal stage as the platform moves from early MVP into scalable production use with enterprise customers. This is a hands-on technical leadership role, not a product management position. You will be responsible for designing, building, and scaling core components of an AI-driven enterprise platform, working across data, machine learning, and distributed systems. You will also work directly with early customers to understand real-world use cases and translate them into robust, scalable product capabilities. This role suits someone who still enjoys building and shipping code, but is comfortable influencing architecture, mentoring engineers, and shaping technical direction.
You will have significant influence over:
- Core system architecture
- AI/ML strategy and implementation
- Data modelling and enterprise integration patterns
- Early product design decisions
- Engineering standards and scalability approach
Key Responsibilities
- Design and build core components of an AI-native enterprise platform from the ground up
- Develop and deploy machine learning and LLM-based systems in production environments
- Build scalable data and AI pipelines across complex enterprise datasets
- Work closely with early enterprise customers to refine requirements and shape product direction
- Define and implement system architecture for AI, data, and integration layers
- Build agentic AI workflows and knowledge-driven systems using modern LLM frameworks
- Implement robust MLOps pipelines for model training, deployment, monitoring, and governance
- Contribute directly to production code in Python and related AI/data tooling
- Support technical decision-making around cloud architecture, scalability, and system design
- Help establish engineering best practices in a fast-moving early-stage environment
Tech Stack
- Python
- TensorFlow / PyTorch
- LLM frameworks (LangChain, LangGraph, or similar agentic AI tooling)
- AWS / Azure cloud platforms (including AI services such as Bedrock)
- Data engineering tools (e.g. AWS Glue or equivalent)
- NLP, embeddings, vector databases, RAG architectures
- MLOps tooling for model deployment and monitoring
Required Skills & Experience
- Several years' experience in software engineering, data engineering, or AI engineering roles
- Strong academic background in Computer Science, Engineering, Mathematics, or similar
- Experience working in a product-led technology environment (SaaS, AI platform, or similar)
- Proven ability to ship production-grade AI or data systems
- Strong Python engineering capability
- Experience with modern ML / LLM systems and frameworks
- Exposure to cloud-based AI/ML platforms (AWS, Azure, or GCP)
- Comfortable working in early-stage environments with ambiguity and ownership
- Strong communication skills and ability to work directly with technical and non-technical stakeholders
Bonus Experience (Highly Valued)
- Cyber security / identity / access management (IAM / IdAM) exposure
- Cloud operations, DevSecOps, or infrastructure-heavy environments
- Experience in regulated or enterprise-scale domains
- Knowledge of enterprise data governance, data modelling, or integration architecture
How You Work
- Highly hands-on and enjoys building systems end-to-end
- Comfortable operating in ambiguity and shaping problems as well as solving them
- Strong bias toward delivery, iteration, and practical engineering outcomes
- Collaborative, but able to take full ownership of technical decisions
- Interested in building foundational systems, not just features
What We Offer
- Highly competitive base salary (DOE) + bonus
- Equity / stock options in a high-growth early-stage business
- Private medical insurance
- Hybrid working (London-based, flexible model)
- High ownership role with significant influence on product and architecture
Founding Engineer in London employer: Oscar
Join an innovative early-stage technology company in London as a Founding AI Engineer, where you'll play a pivotal role in shaping the future of AI-native systems. With a strong focus on ownership and collaboration, you'll enjoy a highly competitive salary, equity options, and the flexibility of hybrid working. This is an exceptional opportunity to influence product direction and architecture while working alongside a small, dedicated team in a dynamic environment that values technical excellence and personal growth.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, tech talks, or even online webinars. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to AI and data engineering. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. But don’t forget to brush up on your soft skills too! Being able to communicate your thought process and collaborate effectively is key in a small, dynamic team.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in our mission. Tailor your application to highlight how your experience aligns with our needs, especially in building scalable AI systems and working in early-stage environments.
We think you need these skills to ace Founding Engineer in London
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and engineering shine through. We want to see that you’re not just looking for a job, but that you’re genuinely excited about building AI-native systems and making an impact in the tech world.
Tailor Your Experience:Make sure to highlight your relevant experience in software engineering, data engineering, or AI engineering. We’re looking for someone who can hit the ground running, so connect your past projects to what we’re doing at StudySmarter and how you can contribute.
Be Clear and Concise:Keep your application clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s necessary. Show us you can explain complex ideas simply, as this is key when working with both technical and non-technical stakeholders.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team at StudySmarter.
How to prepare for a job interview at Oscar
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in the tech stack mentioned in the job description, especially Python, TensorFlow, and any LLM frameworks. Brush up on your knowledge of AWS or Azure services, as you'll likely be asked how you would leverage these tools in real-world scenarios.
✨Showcase Your Hands-On Experience
Prepare to discuss specific projects where you've designed and built AI systems or data pipelines. Be ready to explain your role in these projects, the challenges you faced, and how you overcame them. This will demonstrate your hands-on capability and problem-solving skills.
✨Understand the Business Context
Research the company’s mission and the problems they aim to solve with their AI-native systems. Be prepared to discuss how your experience aligns with their goals and how you can contribute to shaping their product direction and architecture.
✨Communicate Clearly with Technical and Non-Technical Stakeholders
Since this role involves working closely with early customers, practice explaining complex technical concepts in simple terms. Think of examples where you've successfully communicated with both technical teams and non-technical stakeholders to ensure everyone is on the same page.
