Direct message the job poster from Hive Science

Hive Science is a tech start-up whose technologies are in use by many of the world’s 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. We’re 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 Hive’s 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. We’re 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 You’ll Be Doing:

As a Senior Full Stack AI Engineer (R&D), you’ll sit at the heart of the product development process, responsible for end-to-end system integrity—from frontend interfaces to backend APIs, from infrastructure orchestration to LLM security governance, developing and scaling our unique product. You’ll 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 can’t 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 – 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 “hacking” 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. We’re nimble and creative, and value intellectual humility. We work really hard because we’re all 100% dedicated to the future we’re building. Our work is stimulating, challenging, and exciting. And our team is awesome. At Hive we only hire exceptional people, so you’ll be in good company -- surrounded by passionate, insanely smart people who want to build the future of customer intelligence. Specifically we’re looking for someone who will thrive in this type of environment:

• Fast-paced startup with competing demands and multiple priorities ongoing
• A ‘solve the problem’ 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 careers@hivescience.ai

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Technology, Information and Media

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