Site Reliability Engineer

About Lucidya

Lucidya is an AI-native platform for customer experience (CX) intelligence that manages entire customer life cycles autonomously, from initial engagement through retention and growth.

Unlike platforms that only surface insights and leave the action to you, Lucidya closes the loop with proprietary NLU technology built in-house and trained on millions of multilingual conversations. This enables marketing, support, CX, and research teams to deliver personalized experiences that drive measurable improvements in customer satisfaction, retention, and lifetime value.

As we continue scaling globally, the reliability, performance, and resilience of our infrastructure become mission-critical to everything we do.

At Lucidya, our platform processes massive volumes of real-time customer data. Any downtime, latency, or instability directly impacts our customers’ ability to make decisions and serve their own users.

This role exists to make sure that doesn’t happen.

As a Site Reliability Engineer, you’ll sit at the heart of our platform’s stability, owning the reliability of our cloud infrastructure and ensuring it scales seamlessly as we grow. You won’t just react to issues; you’ll anticipate them, design systems that prevent them, and build automation that removes them entirely.

If you enjoy solving complex infrastructure challenges, eliminating inefficiencies, and building systems that “just work” - this is where you’ll thrive.

You’ll be responsible for outcomes, not just tasks. Here’s what success looks like in this role:

You’ll make reliability the default

• You’ll design and maintain infrastructure that is highly available, fault‑tolerant, and scalable
• You’ll proactively identify and eliminate single points of failure before they become incidents

• You’ll ensure our production systems remain stable, even under increasing scale and load

You’ll own and optimize our cloud environments

• You’ll manage and continuously improve workloads across AWS, GCP, or Azure
• You’ll use Infrastructure as Code (Terraform) to standardize and scale infrastructure
• You’ll optimize resource usage to balance performance and cost

You’ll run and improve Kubernetes in production

• You’ll operate and scale Kubernetes clusters (EKS, GKE, etc.) with confidence
• You’ll troubleshoot issues quickly and ensure smooth deployments and upgrades
• You’ll ensure our containerized workloads perform reliably at scale

You’ll build strong observability and respond to incidents

• You’ll implement and refine monitoring systems using tools like Prometheus, Grafana, Datadog, or ELK
• You’ll define alerting that is meaningful, not noisy
• You’ll respond to incidents, lead root cause analysis, and ensure we learn from every failure

You’ll automate everything that shouldn’t be manual

• You’ll write scripts and build tooling to eliminate repetitive operational work
• You’ll continuously improve infrastructure efficiency through automation
• You’ll promote a culture where manual work is a temporary state, not the norm

You’ll collaborate to improve the entire system

• You’ll work closely with Dev Ops and engineering teams to solve performance bottlenecks
• You’ll contribute to CI/CD improvements and deployment reliability
• You’ll help shape reliability best practices across the organization

First 30 days:

• You’ve built a strong understanding of our infrastructure, systems, and workflows
• You’re contributing to day‑to‑day operations with support from the team
• You’ve started identifying areas for improvement in automation and reliability

By 90 days:

• You’re independently managing infrastructure tasks and troubleshooting issues
• You’re actively contributing to reliability and scalability improvements
• You’ve taken ownership of parts of our infrastructure and are improving them

This is what will make you successful in this role:

• You’ve spent ~3 years working in SRE, Dev Ops, or infrastructure engineering, and you’ve seen what breaks at scale
• You’re comfortable working in cloud environments like AWS, GCP, or Azure—and you understand how distributed systems behave
• You’ve worked hands‑on with Kubernetes in production and know how to…