About the role:
NLPatent is seeking a Senior DevSecOps / DevOps Engineer with expertise in AWS to join our growing team. In this crucial role, you will be responsible for provisioning and maintaining our cloud infrastructure as well as implementing security practices across our infrastructure, ensuring that security is integrated throughout the development lifecycle. You will work closely with development and IT teams to automate and streamline operations and processes, helping us build secure, scalable, and reliable applications.
Your contributions will directly impact our ability to deliver secure and efficient services while maintaining high availability for our users.
Requirements
- 5+ years of experience in DevOps or related field
- Strong knowledge of cloud-native architecture principles
- Deep understanding of AWS services and architecture
- Experience with infrastructure as code (e.g., Terraform, CloudFormation)
- Proficiency in CI/CD tools and practices
- Strong knowledge of security best practices and compliance in cloud environments
- Proficient with containerization technologies (e.g., Docker, Kubernetes)
- Experience with monitoring and logging tools (e.g., CloudWatch, Datadog)
- Ability to work 3 days a week onsite in our London office
- Experience with building systems in accordance with major security standards (e.g. SOC 2, ISO 27001)
- Experience with serverless architecture and services (e.g., AWS Lambda)
- Familiarity with Agile methodologies
- Experience with GitOps practices
- Ability to mentor junior team members and share security best practices
Benefits
- Base salary of £65k-£75k (dependent on experience and performance in technical assessments)
- Flexible working
- Pension
- Training & Development
- Stock Option Plan
- 25 days holiday per year
Top Skills
What We Do
NLPatent is an industry leading AI-based patent search and analytics platform trusted by Fortune 500 companies, Am Law 100 firms, and research universities around the world. The platform takes an AI-first approach to patent search; it's built from a proprietary Large Language Model trained on patent data to truly understand the language of patents and innovation. Users simply describe their invention in full sentences and conceptually relevant results are generated instantly; consistently outperforming human experts on speed and accuracy. The system is simple, intuitive, and iterative. Best of all, it explains the relevant sections of each patent it identifies, removing the "black box" often experienced by other AI-based platforms.
