[Hiring] Cloud Engineer (Platform & Infrastructure) @Gather AI

Role Description

We are looking for a Cloud Engineer (Platform & Infrastructure) to help mature our cloud operations into a structured and scalable platform. Our foundational infrastructure is already in place and actively supporting production workloads, but many current practices evolved organically during earlier growth stages. Rather than building from scratch, you'll evolve an existing production environment by introducing stronger operational patterns, improving deployment safety, and ensuring our infrastructure layer reliably supports increasing system scale. This role offers meaningful ownership of the infrastructure backbone supporting a platform that combines real-time application systems with machine learning workloads, and the opportunity to influence how systems are deployed, operated, and scaled as the organization grows.

What You'll Do

• Review and rationalize current Azure and AWS environments, identifying configuration drift, security gaps, and operational inconsistencies, and establish clear configuration standards across cloud accounts.
• Introduce repeatable Infrastructure-as-Code patterns to ensure cloud resources are provisioned, versioned, and audited through automated workflows.
• Strengthen CI/CD pipelines for infrastructure and application deployment to reduce manual operations and increase release safety across both application services and ML workloads.
• Establish consistent logging, metrics, and alerting practices across infrastructure and container workloads to improve operational visibility.
• Audit and improve cloud security practices including IAM policies, secrets management, network segmentation, and operational access controls.
• Evaluate current infrastructure architecture and introduce patterns that enable workloads to operate portably across both Azure and AWS environments.
• Improve Kubernetes platform reliability by refining autoscaling policies, workload isolation, and cluster lifecycle management.
• Partner with Fullstack and ML teams to reduce infrastructure friction around environments, networking, and resource provisioning.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience operating production cloud infrastructure at scale.
• Deep experience with at least one major cloud provider (Azure or AWS) and working familiarity with the other.
• Hands-on experience with Kubernetes and Docker for running containerized workloads in production environments.
• Proficiency with Terraform or equivalent Infrastructure-as-Code tooling for provisioning and managing cloud infrastructure.
• Experience implementing automated deployment pipelines using tools such as GitHub Actions, GitLab CI, or similar platforms.
• Strong operational mindset with a focus on reliability, automation, and clear technical documentation.

Nice to Have

• Experience with observability tooling such as Prometheus, ELK, OpenTelemetry, or similar logging, metrics, and monitoring systems.
• Familiarity supporting ML infrastructure workloads including pipeline orchestration, model deployment, and scalable inference environments.
• Experience working in logistics, robotics-adjacent platforms, or real-time distributed systems.
• Track record of translating application requirements into secure, reliable, and operationally safe infrastructure architecture.
• Exposure to cloud cost visibility and optimization practices.
• Experience introducing infrastructure governance standards including templates, security baselines, and operational documentation.