About Lucidya

Lucidya is an AI-native platform for customer experience (CX) intelligence that manages entire customer lifecycles 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.

Why this role matters

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.

What You’ll Do

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 DevOps 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

What success looks like (First 90 Days)

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

Requirements

Who You Are

This is what will make you successful in this role:

You’ve spent ~3 years working in SRE, DevOps, 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 troubleshoot it when things go wrong
You don’t just fix issues - you ask why they happened and make sure they don’t happen again

Technically, you likely:

Use Terraform (or similar IaC tools) to manage infrastructure
Work confidently with Docker and Kubernetes
Write scripts in Python, Bash, or similar to automate workflows
Understand CI/CD pipelines (Jenkins, GitHub Actions, Bitbucket, etc.)
Have a solid grasp of networking, load balancing, and high-availability design

When it comes to monitoring:

You’ve implemented tools like Prometheus, Grafana, Datadog, or ELK
You know the difference between useful alerts and noise
You focus on signals that actually drive action

What sets you apart:

You take ownership - you don’t wait to be told something is broken
You’re calm under pressure and methodical during incidents
You simplify complexity instead of adding to it
You communicate clearly, even when explaining deeply technical issues
You care about building systems that make other engineers more effective

Nice to Have (but not required)

Experience with RabbitMQ or Redis in production
Familiarity with Ansible or AWX
Exposure to multi-cloud or hybrid environments
Cloud certifications (AWS, GCP) or Linux certifications
Background from ITI (Information Technology Institute)

What the hiring process will look like

Screening Interview – Talent Acquisition
Technical Interview – SRE Lead
Technical Task
Final Interview – SRE Lead & Cloud DevOps Director

Originally posted on Himalayas

Senior Cloud Infrastructure Engineer GCP

Job Description