Tech Stack
Job Description, Responsibilities & Requirements
About the Position
Lead GCP DevOps Engineer (AI-Enabled Platform)
In this role, you will design and evolve cloud-native platforms on Google Cloud Platform, helping global organizations modernize infrastructure, accelerate software delivery, and improve operational resilience.
Working within our Cloud and DevOps Practice, you'll collaborate with experienced engineers and architects to deliver secure, scalable, and AI-ready solutions while shaping engineering best practices across projects.
Responsibilities
- Design, build, and operate scalable, secure, and reliable cloud infrastructure on Google Cloud Platform
- Lead or support migration initiatives from other clouds to GCP, ensuring service continuity, security, and cost optimization
- Build, maintain, and continuously improve CI/CD pipelines and deployment automation
- Develop and manage infrastructure using Terraform and Infrastructure as Code best practices
- Deploy, manage, and optimize containerized applications using Kubernetes and Docker
- Implement monitoring, logging, and alerting solutions to ensure platform reliability and performance
- Collaborate with software engineers, architects, and AI/ML teams to deliver cloud-native and AI-enabled solutions
- Support GPU-based infrastructure and AI workloads where applicable
- Implement cloud security best practices, including IAM, secrets management, encryption, and vulnerability management
- Troubleshoot complex production issues and drive continuous platform improvements
- Share technical expertise, mentor team members, and contribute to architecture and engineering best practices
Requirements
- Strong hands-on experience in DevOps, Platform Engineering, or Site Reliability Engineering
- Proven experience designing, implementing, and operating solutions on Google Cloud Platform (GCP)
- Strong experience with Kubernetes (GKE preferred) and Docker in production environments
- Experience building and maintaining CI/CD pipelines using GitHub Actions, Argo CD, or similar CI/CD tools
- Hands-on experience with Infrastructure as Code tooling
- Solid understanding of cloud networking, including Virtual Networks, DNS, load balancing, IAM, VPNs, and security best practices
- Experience implementing monitoring, logging, and observability solutions (e.g., Prometheus, Grafana, Datadog, or similar tools)
- Proficiency in scripting and automation using Python, Go, or Bash
- Strong troubleshooting and problem-solving skills across cloud infrastructure and distributed systems
- Upper-Intermediate or higher English level for effective communication in a global environment
- Experience supporting AI-enabled platforms or machine learning infrastructure and/or familiarity with Vertex AI, Kubeflow, MLflow, Ray, or similar AI/ML platforms would be appreciated
- Familiarity with NVIDIA technologies, including GPU-enabled infrastructure, NVIDIA GPU Operator, CUDA, or NVIDIA AI Enterprise (nice to have)
- Experience providing technical leadership, mentoring engineers, and driving technical decisions (would be an advantage)
- Experience migrating enterprise workloads between clouds (is a plus)
- Experience in designing infrastructure architectures (would be desirable)
We Offer
Flexible Work Model
Work from home, from the office, or in a hybrid format that supports focus and collaboration.
Compensation & Benefits
Competitive, market-based pay, benchmarked by role and location - plus health coverage, paid time off, wellness support, and learning opportunities.
People-first Leadership
Approachable leaders who communicate openly, keep teams close to the strategy, and support long-term planning.
Advanced tech communities
Stay close to AI/ML, Cloud, Quantum Computing, IoT, and Robotics communities, with projects built on modern frameworks.
About the Company
We are a digital engineering and technology consulting company where expertise grows alongside people. For more than 30 years, we have been elevating technology: helping organizations navigate complex business challenges by combining deep engineering knowledge with thoughtful, research-backed innovation. Our teams work across key areas: digital engineering, data and analytics, Cloud, and AI/ML. In each, we deliver practical, scalable solutions rooted in real business needs and measurable human impact.
You bring your perspective and ambition. We create an environment where your work meets clarity, confidence, and purpose.