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- Tasks: Join our product team as a Senior Full Stack AI Engineer, evolving cutting-edge tech.
- Company: Hive Science is a dynamic startup transforming work with AI and behavioural science.
- Benefits: Enjoy a fast-paced environment, collaborate with brilliant minds, and make a real impact.
- Why this job: Be at the forefront of AI innovation while working in a creative, supportive culture.
- Qualifications: Strong backend skills in Python, cloud infrastructure experience, and a passion for AI required.
- Other info: This is an in-person role based in London; remote candidates will not be considered.
The predicted salary is between 84000 - 126000 ÂŁ per year.
Direct message the job poster from Hive Science
Hive Science is a tech start-up whose technologies are in use by many of the worldâs largest brands including Land Rover, Edward Jones & Kroger. The Hive platform is delivering novel intelligence at the intersection of quantitative social psychology, behavioral science & AI/ML to accelerate & transform how work is done. Weâre looking for someone to join our team and get on board this rocket ship with us.
About the role:
This is an exciting opportunity to be part of a psychological science-based tech startup. This role will join our product team and will be responsible for evolving Hiveâs next generations of products. This Senior Full Stack AI Engineer will roll up their sleeves and help us continually evolve the core foundation of our platform, enabling exponential delivery speed and scale, as well as new generative and other AI technologies. Weâre looking for someone who can bring a strong AI know-how, and who can work closely with social science data to support product development & launch.
What Youâll Be Doing:
As a Senior Full Stack AI Engineer (R&D), youâll sit at the heart of the product development process, responsible for end-to-end system integrityâfrom frontend interfaces to backend APIs, from infrastructure orchestration to LLM security governance, developing and scaling our unique product. Youâll be part of a SWAT team located in London. You will build prototypes, move quickly, but be ready to scale and productionise once breakthroughs are made into our commercial product.
You will constantly need to be at the cutting edge as we plug and play the latest AI capabilities into our core platform. We canât define everything you will be doing because some of it is unknown based on the disruptive world we live in and you need to be the kind of person ready to pivot at speed and stay at the bleeding edge of this new world.
Key areas of responsibility include:
Full Stack Engineering:
- Architect and build modern web applications with responsive, performant UIs (React/Vue) and robust, secure backends (Python/Node/Java).
- Design and maintain RESTful and GraphQL APIs, connecting frontend, backend, and ML / DL (LLMS â RAG / GraphRAG, Generative services).
- Create user interfaces and back-end pipelines for exploring generative content, insights, and AI-powered workflows.
DevOps & Infrastructure
- Lead the setup and ongoing management of dev/staging/production environments with CI/CD pipelines to automate testing, builds, and deployments.
- Provision infrastructure via Infrastructure-as-Code (Terraform, CloudFormation).
- Implement monitoring, uptime tracking, and alerting systems (e.g., Prometheus,
- CloudWatch, Grafana) to maintain system reliability.
Security & Governance
- Harden the platform with secure coding practices, firewalls, role-based access, encryption at rest and in transit, and secrets management (e.g., AWS Secrets Manager).
- Develop and enforce governance best practices for working with LLM APIs, including data redaction, prompt injection protection, and PII safeguards.
AI & ML Integration
- Work with the data scientists to productionise models (e.g., text/image embeddings, recommender systems, LLMs, CLIP).
- Build tools for integrating and orchestrating LLMs, computer vision / NLP pipelines, and generative workflows into the product experience.
- Support ETL workflows for preparing training and inference data; collaborate on knowledge graph structuring.
Required Skills & Experience:
- Strong backend skills: Python (FastAPI/Flask), SQL, Node.js, or Java-based APIs
- Strong experience provisioning secure cloud infrastructure (AWS preferred, also GCP or Azure)
- Strong experience with cloud platforms (AWS, Databricks, Snowflake), containerisation tools (Docker, Kubernetes), and CI/CD pipelines, MLOps and model deployment (GitHub Actions, CircleCI, Jenkins).
- Strong experience with cloud-native ML workflows, including AWS Sagemaker, Lambda, ECS, and containerisation with Docker.
- Proficiency in database design and scaling: SQL, NoSQL, vector DBs (e.g., Pinecone, FAISS), and graph DBs (e.g., Neo4j)
- Strong ETL and data pipeline experience
- Strong experience with LLMs, computer vision (e.g., CLIP), NLP and Gen AI workflows
- Familiarity with secrets management, access control, and IAM configuration
- Comfort with scripting and automation (Bash, Python)
- Monitoring tool fluency (CloudWatch, Prometheus/Grafana, Sentry, etc.)
- Previous work in early-stage product teams or high-growth startups
- Comfort in âhackingâ prototypes while planning toward scalable solutions.
- Passion for elegant production ready code
Overall Work Experience & Additional Details:
You may have come from a research lab or from a startup where you wore every hat. You are fluent in both theory and implementation, and you get a thrill out of connecting ML / DL research to real-world product needs.
As a fast-paced startup, each day is different from the one before. Weâre nimble and creative, and value intellectual humility. We work really hard because weâre all 100% dedicated to the future weâre building. Our work is stimulating, challenging, and exciting. And our team is awesome. At Hive we only hire exceptional people, so youâll be in good company — surrounded by passionate, insanely smart people who want to build the future of customer intelligence. Specifically weâre looking for someone who will thrive in this type of environment:
- Fast-paced startup with competing demands and multiple priorities ongoing
- A âsolve the problemâ mentality
- Scrappy and creative
- Strong passion for the Hive Science mission and a love of the scientific method
This is an in-person role in London, UK – we cannot consider candidates who do not currently live within commuting distance.
To apply, please send resume to
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Senior Full Stack AI Engineer employer: Hive Science
Contact Detail:
Hive Science Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior Full Stack AI Engineer
â¨Tip Number 1
Familiarise yourself with the latest AI and ML technologies that are relevant to the role. Being able to discuss recent advancements or tools you've used in your projects can really impress the team at Hive Science.
â¨Tip Number 2
Showcase your experience with full stack development by preparing a portfolio of projects that highlight your skills in both frontend and backend technologies. This will demonstrate your capability to handle the end-to-end system integrity theyâre looking for.
â¨Tip Number 3
Engage with the Hive Science community on platforms like LinkedIn or GitHub. By connecting with current employees or contributing to discussions, you can gain insights into their culture and values, which can help you tailor your approach during interviews.
â¨Tip Number 4
Prepare to discuss how you would tackle real-world problems using AI and ML in a startup environment. Think of examples where you've had to pivot quickly or innovate under pressure, as this aligns with the fast-paced nature of Hive Science.
We think you need these skills to ace Senior Full Stack AI Engineer
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Focus on your full stack engineering capabilities, AI/ML integration, and any experience with cloud infrastructure.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the Hive Science mission and your problem-solving mentality. Mention specific projects or experiences that demonstrate your ability to thrive in a fast-paced startup environment.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially those mentioned in the job description such as Python, SQL, Node.js, and experience with CI/CD pipelines. Use examples to illustrate your proficiency.
Highlight Team Collaboration: Emphasise your experience working in product teams or startups. Discuss how youâve collaborated with data scientists or other engineers to bring projects from concept to production, showcasing your ability to work in a dynamic team setting.
How to prepare for a job interview at Hive Science
â¨Showcase Your Full Stack Skills
Make sure to highlight your experience with both frontend and backend technologies. Be prepared to discuss specific projects where you've built modern web applications, detailing the frameworks and languages you used, such as React or Python.
â¨Demonstrate Your AI Knowledge
Since this role heavily involves AI and ML, come ready to discuss your familiarity with LLMs, computer vision, and generative workflows. Share examples of how you've integrated these technologies into previous projects.
â¨Emphasise Your Problem-Solving Mindset
Hive Science values a 'solve the problem' mentality. Prepare to discuss challenges you've faced in past roles and how you approached them creatively. This will show that you're adaptable and can thrive in a fast-paced startup environment.
â¨Prepare for Technical Questions
Expect technical questions related to cloud infrastructure, CI/CD pipelines, and security practices. Brush up on your knowledge of AWS, Terraform, and secure coding practices to demonstrate your expertise during the interview.
