At a Glance
- Tasks: Build and scale innovative infrastructure for cutting-edge AI products.
- Company: Join a dynamic psychological science-based tech startup in London.
- Benefits: Competitive salary, vibrant team culture, and opportunities for growth.
- Other info: Fast-paced environment with passionate colleagues and exciting challenges.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: Experience in cloud infrastructure, automation, and DevOps best practices.
The predicted salary is between 63000 - 77000 £ per year.
This is an exciting opportunity to be part of a psychological science-based tech startup.
This role sits within our product team and will be responsible for building, maintaining, and scaling the infrastructure that powers Hive’s scalable products.
This Dev Ops Engineer will roll up their sleeves and help us continually evolve the foundation of our platform, enabling faster delivery speed and greater scale, as well as supporting new generative AI and machine learning technologies.
We’re looking for someone who can bring strong infrastructure and automation expertise, and who can work closely with engineering and data science teams to support rapid product development & launch.
What You’ll Be Doing
As a Dev Ops Engineer (Product), you’ll be responsible for the reliability, scalability, and security of our entire infrastructure stack; from CI/CD pipelines to production deployments, from infrastructure orchestration to security governance.
You’ll be part of a high-powered team located in London.
You will build robust systems, move quickly, but be ready to scale and ensure production-grade reliability as our product grows.
You will constantly need to be at the cutting edge as we deploy and scale the latest AI capabilities within 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.
- Infrastructure & Cloud Engineering
- Design, provision, and manage scalable cloud infrastructure using Infrastructure-as-Code (Terraform, Cloud Formation) across AWS (must have deep experience), GCP, or Azure.
- Architect and maintain highly available, fault-tolerant systems that support our AI/ML workloads, web applications, and data pipelines.
- Manage containerization and orchestration platforms (Docker, Kubernetes, ECS) to support microservices and ML model deployments.
- CI/CD & Automation
- Build and maintain robust CI/CD pipelines (Git Hub Actions, Circle CI, Jenkins) to automate testing, builds, and deployments across dev/staging/production environments.
- Implement MLOps workflows to streamline model deployment, versioning, and monitoring for our AI/ML products.
- Automate infrastructure provisioning (Terraform), configuration management, and deployment processes using scripting (Bash, Python) and automation tools.
- Monitoring, Observability & Reliability
- Implement comprehensive monitoring, logging, and alerting systems (Prometheus, Grafana, Cloud Watch, Datadog, Sentry) to ensure system reliability and rapid incident response.
- Establish SLOs/SLIs and implement observability best practices to maintain high availability and performance.
- Lead incident response, root cause analysis, and implement preventive measures to improve system resilience.
- Security & Governance
- Implement and maintain security best practices including network security, firewalls, role-based access control (IAM), encryption at rest and in transit, and secrets management (AWS Secrets Manager, Hashi Corp Vault).
- Develop and enforce governance frameworks for working with LLM APIs and AI services, including data protection, PII safeguards, and compliance requirements.
- Conduct security audits, vulnerability assessments, and implement remediation strategies to maintain a secure infrastructure.
- Collaboration & Technical Support
- Work closely with full-stack engineers and data scientists to support application deployments, optimize performance, and troubleshoot infrastructure issues.
- Support ETL/ELT workflows and data pipeline infrastructure for training and inference workloads across databases (SQL, No SQL, Vector DBs, Graph DBs).
- Provide technical guidance and mentorship on Dev Ops best practices, infrastructure design, and deployment strategies.
- Strong experience provisioning and managing secure cloud infrastructure (AWS preferred, also GCP or Azure)
- Expertise with Infrastructure-as-Code tools (Terraform, Cloud Formation, Pulumi)
- Strong experience with containerization and orchestration (Docker, Kubernetes, ECS, Fargate)
- Proven track record building and maintaining CI/CD pipelines (Git Hub Actions, Circle CI, Jenkins, Git Lab CI)
- Experience with MLOps and supporting ML model deployment workflows (AWS Sagemaker, Lambda, containerized deployments)
- Proficiency in scripting and automation (Python, Bash, Go)
- Strong experience with monitoring and observability tools (Cloud Watch, Prometheus, Grafana, Datadog, Sentry, New Relic)
- Experience with database administration and optimization across SQL, No SQL, vector databases (Pinecone, FAISS), and graph databases (Neo4j)
- Knowledge of networking, security best practices, IAM configuration, and secrets management
- Experience supporting data pipelines, ETL workflows, and cloud data platforms (Databricks, Snowflake)
- Strong experience with the set up / design / governance and security of Clean Rooms and clean room integrations
- Previous experience in early-stage product teams or high-growth startups
- Ability to balance rapid prototyping with building scalable, production-grade infrastructure
- Strong problem-solving skills and ability to work independently in a fast-paced environment
- Overall Work Experience
You may have come from a platform engineering team at a tech company or from a startup where you wore every hat.
You are fluent in both infrastructure theory and hands-on implementation, and you get a thrill out of building reliable, scalable systems that enable rapid product innovation and support cutting-edge AI/ML workloads.
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
- Own critical infrastructure decisions that directly shape the products we build
- 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.
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DevOps Engineer (Product) in London employer: Hive Science
At Hive, we pride ourselves on being a fast-paced startup that thrives on creativity and innovation. Our London-based team is dedicated to building the future of customer and marketing intelligence, offering a stimulating work environment where every day presents new challenges and opportunities for growth. We value intellectual humility and are committed to hiring exceptional talent, ensuring that you will be surrounded by passionate and highly skilled colleagues who share your enthusiasm for pushing the boundaries of AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land DevOps Engineer (Product) in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Hive Science or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Hive Science.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Hive Science.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Hive Science that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace DevOps Engineer (Product) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Hive Science.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Hive Science and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Hive Science
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Hive Science uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.