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 Senior DevOps 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.

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What You’ll Be Doing:

As a Senior DevOps 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.

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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.

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Infrastructure & Cloud Engineering:

• Design, provision, and manage scalable cloud infrastructure using Infrastructure-as-Code (Terraform, CloudFormation) 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.

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CI/CD & Automation:

• Build and maintain robust CI/CD pipelines (GitHub Actions, CircleCI, 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.

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Monitoring, Observability & Reliability:

• Implement comprehensive monitoring, logging, and alerting systems (Prometheus, Grafana, CloudWatch, 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.

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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, HashiCorp 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.

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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, NoSQL, Vector DBs, Graph DBs).
• Provide technical guidance and mentorship on DevOps best practices, infrastructure design, and deployment strategies.

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