About Lucidya
Lucidya is an AI-native Customer Experience Intelligence platform enabling enterprises to understand, engage, and retain customers at scale. Unlike tools that just surface insights, Lucidya completes the loop with proprietary AI capabilities, helping teams take action and improve customer experiences across marketing, support, and research.
As we scale globally, building reliable, scalable, and automated infrastructure is a top priority. DevOps is a core pillar of our engineering strategy, and we are investing heavily in deployment pipelines, observability, and operational efficiency across all products.
Why This Role Matters
Our engineering teams deliver fast-moving, AI-driven products, and the backbone of their speed and reliability is solid infrastructure and automation. As a DevOps Engineer, you’ll ensure our systems scale seamlessly, deployments happen without friction, and incidents are caught before they impact users. You’ll enable our teams to move faster, focus on building features, and trust that the platform is rock-solid.
You’ll be part of shaping the operational culture at Lucidya, where automation, reliability, and proactive problem solving aren’t just buzzwords, they’re outcomes we obsess over every day.
What You’ll Do
- Build, maintain, and improve CI/CD pipelines to support reliable and efficient software delivery.
- Deploy and manage containerized applications using Docker and Kubernetes.
- Support cloud infrastructure management and automation using Infrastructure as Code tools such as Terraform.
- Implement and maintain monitoring, logging, and alerting solutions using tools such as Grafana.
- Automate repetitive operational tasks and support development teams with infrastructure and deployment needs.
- Troubleshoot deployment, application, and infrastructure issues, identifying root causes and implementing solutions.
- Collaborate with engineers to improve system performance, reliability, and release processes.
- Follow security best practices across deployment pipelines, applications, and infrastructure.
- Participate in incident investigation and resolution, escalating complex issues when necessary.
- Contribute to documentation and continuous improvement of infrastructure workflows and operational processes.
Day-to-Day You’ll:
- Deploy applications and support routine operations within Kubernetes environments.
- Build, maintain, and troubleshoot CI/CD pipelines for new and existing services.
- Monitor system health, investigate alerts, and resolve common deployment and infrastructure issues.
- Support developers with application deployments, environment configurations, and infrastructure requests.
- Write and maintain scripts to automate repetitive operational tasks.
- Assist with infrastructure provisioning and configuration management.
- Collaborate with senior engineers to investigate complex incidents and improve system reliability.
- Continuously identify opportunities to improve automation, observability, and operational efficiency.
Success Looks Like:
- Reliable CI/CD pipelines with fewer deployment failures and smoother releases.
- Successful deployment and operation of containerized applications in Kubernetes.
- Faster identification and resolution of common infrastructure and deployment issues.
- Reduced manual operational effort through automation.
- Improved monitoring, logging, and visibility into application health.
- Effective collaboration with engineering teams and clear documentation of operational processes.
First 90 Days
- 0–30 Days: Understand Lucidya’s infrastructure, architecture, deployment workflows, tools, and operational practices. Become familiar with existing cloud environments and Kubernetes deployments.
- 30–60 Days: Contribute to CI/CD pipeline improvements, support routine deployments, troubleshoot common issues, and take ownership of smaller infrastructure tasks with guidance from senior engineers.
- 60–90 Days: Successfully onboard 2–3 services onto the existing Kubernetes environment, with appropriate CI/CD pipelines, monitoring, and health checks, collaborating with senior engineers where needed.
Requirements
Who You Are
- Experienced: You have 5–7 years of hands-on experience in DevOps, Cloud Infrastructure, Platform Engineering, or a related role.
- Hands-On: You have practical experience with CI/CD pipelines, Docker, Kubernetes, and cloud infrastructure.
- Proactive Problem Solver: You can investigate common technical issues, identify root causes, and implement solutions while knowing when to escalate complex problems.
- Collaborative: You work closely with developers and other engineers to support deployments and improve infrastructure reliability.
- Curious & Growth-Oriented: You are eager to learn, improve existing systems, and develop your expertise in cloud infrastructure, automation, and observability.
- Quality-Focused: You understand the importance of reliable deployments, infrastructure security, monitoring, and operational documentation.
Technical Skills You’ll Bring
- CI/CD: Hands-on experience building, maintaining, or improving CI/CD pipelines using tools such as GitHub Actions, GitLab CI/CD, Jenkins, or similar.
- Containers & Orchestration: Practical experience with Docker and working knowledge of Kubernetes, including application deployments, configurations, and troubleshooting.
- Infrastructure as Code: Familiarity with Terraform, CloudFormation, or similar tools for provisioning and managing infrastructure.
- Cloud Platforms: Hands-on experience with at least one major cloud provider, such as AWS or GCP.
- Scripting & Automation: Ability to write basic automation scripts using Bash or Python.
- Monitoring & Observability: Familiarity with monitoring, logging, and alerting tools such as Grafana, Prometheus, or similar.
- Configuration Management: Basic knowledge of tools such as Ansible, Puppet, or Chef.
- Linux & Networking: Working knowledge of Linux systems, networking fundamentals, DNS, HTTP/HTTPS, and troubleshooting connectivity issues.
- Version Control: Experience using Git and working with collaborative software development workflows.
- Experience working in a SaaS, product-based, or AI-driven environment.
- Exposure to production Kubernetes environments and container orchestration.
- Familiarity with advanced monitoring, observability, and incident management practices.
- Understanding of cloud security, secrets management, and infrastructure access controls.
- Experience optimizing deployment workflows and improving infrastructure reliability.
- Python knowledge is a must, Software background is mandatory
Nice-to-Haves
- Experience optimizing AI deployment workflows & MlOps practices.
- Experience optimizing GPU usage for AI workload.