Tilda Research
Website:
tilda.bio
Job details:
Remote
We are looking for an experienced DevOps Engineer with a strong focus on production performance, reliability, security, and automation. This person will play a critical role in maintaining and improving our production environments while helping engineering teams build and operate scalable, secure, and high-performing systems.
The ideal candidate has 4–10 years of DevOps, SRE, Platform Engineering, or Cloud Infrastructure experience, strong hands-on Kubernetes expertise, experience with modern monitoring and observability tools, and an interest in using AI-powered tools and automation to improve engineering operations.
We are looking for someone who enjoys solving difficult production problems, takes ownership, and is enthusiastic about making a measurable difference.
What You’ll Do
Production Reliability & Performance
- Maintain, support, and continuously improve highly available production environments.
- Monitor application and infrastructure performance and proactively identify bottlenecks, reliability issues, and opportunities for optimization.
- Troubleshoot complex production issues across infrastructure, applications, Kubernetes, networking, and cloud services.
- Improve system availability, scalability, resiliency, and overall production performance.
- Participate in incident response, root cause analysis, and post-incident improvements.
- Help establish and improve operational standards around system health, performance, and reliability.
Kubernetes & Cloud Infrastructure
- Build, operate, maintain, and optimize Kubernetes environments running production workloads.
- Manage containerized applications and services using Kubernetes and Docker.
- Support scaling, cluster performance, service availability, upgrades, and troubleshooting.
- Design and maintain scalable cloud infrastructure primarily in AWS and/or GCP.
- Use Infrastructure as Code technologies such as Terraform, CloudFormation, or Pulumi to automate infrastructure provisioning and configuration.
Monitoring & Observability
- Implement and improve monitoring, alerting, logging, tracing, and observability across production systems.
- Work with a variety of modern monitoring and observability platforms to understand infrastructure and application health.
- Build dashboards, alerts, and operational metrics that help teams identify issues before they impact customers.
- Use production data to identify performance trends and drive continuous improvement.
- Help engineering teams improve visibility into their applications and services.
Security & DevSecOps
- Build security into infrastructure, deployment pipelines, and production operations.
- Partner with engineering and security teams on IAM, secrets management, vulnerability remediation, infrastructure hardening, and secure configuration.
- Identify infrastructure and production security risks and help drive remediation.
- Apply DevSecOps practices throughout the software development and deployment lifecycle.
- Balance security requirements with system performance, reliability, and developer productivity.
AI, Automation & Developer Productivity
- Leverage AI-powered engineering and operations tools to improve troubleshooting, monitoring, automation, and operational efficiency.
- Evaluate opportunities to use AI to identify anomalies, analyze logs, accelerate incident investigation, and automate repetitive operational tasks.
- Automate manual infrastructure and production processes wherever practical.
- Improve internal tooling and developer workflows.
- Help create self-service capabilities that allow engineering teams to operate more efficiently.
CI/CD & Release Engineering
- Build, maintain, and optimize CI/CD pipelines across multiple environments.
- Improve deployment reliability, release automation, and rollback capabilities.
- Partner with software engineers to improve the software delivery lifecycle.
- Support modern deployment strategies including blue/green and canary deployments.
What We’re Looking For
- 4–10 years of hands-on DevOps, SRE, Platform Engineering, Cloud Infrastructure, or similar experience.
- Strong experience with Argo CD is required
- Strong experience maintaining and troubleshooting production environments.
- Strong hands-on experience with Kubernetes and containerized production workloads.
- Experience working within AWS and/or GCP cloud environments.
- Experience with Infrastructure as Code, preferably Terraform.
- Strong experience with monitoring, observability, logging, and alerting tools.
- Experience troubleshooting production performance and reliability issues.
- Solid understanding of cloud and infrastructure security best practices.
- Experience with CI/CD pipelines and modern software deployment practices.
- Experience using—or a strong interest in using—AI tools within DevOps, SRE, infrastructure, or production operations.
- Strong troubleshooting and problem-solving skills.
- Ability to take ownership of production issues and work effectively across engineering teams.
- Enthusiastic, curious, and motivated by opportunities to make a meaningful difference.
Preferred Background
- Experience working for a product-based SaaS or technology company.
- Experience supporting internally developed software products or platforms in production.
- Experience operating Kubernetes at meaningful production scale.
- Familiarity with monitoring and observability technologies such as Datadog, Grafana, Prometheus, New Relic, Splunk, Elastic, CloudWatch, or similar platforms.
- Experience with application performance monitoring (APM), distributed tracing, and production performance optimization.
- Experience incorporating security scanning, vulnerability management, or policy enforcement into CI/CD and infrastructure workflows.
- Exposure to AI-assisted operations, AIOps, AI coding tools, or AI-driven infrastructure/observability platforms.
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