Senior Cloud Infrastructure Engineer
Senior Cloud Infrastructure Engineer
Posted today
SENIORITY
Lead
About the role
- Lead infrastructure architecture decisions and guide best practices for cloud systems and deployment workflows
- Design and implement cost-effective AWS infrastructure for deploying and operating vision and language models
- Build and maintain scalable systems for data storage, processing, and analytics
- Maintain, improve, and scale existing cloud infrastructure and services
- Identify inefficient deployment patterns and implement improvements to increase reliability and reduce operational cost
- Design and implement scalable CI/CD pipelines to support rapid and reliable deployments
- Maintain and scale relational and time-series database infrastructure
- Develop and maintain infrastructure-as-code using OpenTofu and related tooling
- Improve observability, monitoring, and operational tooling across cloud services and applications
- Work with engineering teams to ensure infrastructure supports performance, reliability, and security requirements
- 5+ years of experience building and operating production software or infrastructure systemsStrong experience designing and operating cloud infrastructure, preferably on AWSExperience building and maintaining infrastructure-as-code using tools such as OpenTofu, Terraform, or similar frameworks
- Experience developing infrastructure, automation, or backend services in Python or similar programming languages
- Experience designing and operating scalable systems for data processing, machine learning workloads, or high-throughput services
- Experience building or maintaining CI/CD pipelines and deployment automation
- Familiarity with relational databases and time-series data systemsStrong understanding of system reliability, observability, and performance optimization
- Ability to identify inefficiencies in systems and improve scalability, reliability, and cost efficiency
- Strong communication and collaboration skills and ability to work across engineering teams
- Domain knowledge in aviation, autonomous systems
- Experience deploying or supporting machine learning models in production environmentsExperience supporting computer vision or large language model workloads
- Experience operating large-scale cloud infrastructure in cost-sensitive environmentsExperience working in early-stage startups or fast-moving engineering teams
- Experience with distributed systems and high-volume data pipelines
- Opportunity to work on meaningful problems in aviation and deliver products to industry at a rapid pace
- Small team with significant impact on company direction
- Collaborative and innovative environment
- Competitive compensation and benefits
- Opportunities for growth and leadership
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
