DevOps Engineer

ZentixSoft is looking for a Senior AI Infrastructure Architect (GCP, GKE & MLOps) 🧠⚙️
 

We are expanding our high-performance computing and MLOps direction for our international partners and are looking for a mature Senior AI Infrastructure Architect to design scalable, GPU-accelerated cloud environments in the security and urban intelligence sector.

Note: This is an Outstaffing role.
 

💡 Why ZentixSoft? 
💸 Salary Review: A structured system of compensation reviews aligned with your expertise and engineering growth. 
⚖️ Work-Life Balance: A focus on sustainable engineering practices with no senseless overtime, helping you keep your resource fully charged. 
🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy. 🎁 Gifts & Culture: Corporate gifts for birthdays, and a true team atmosphere where your voice always matters.
 

If you are ready to architect next-generation AI platforms, here is what our perfect match looks like:

1️⃣ Cloud & K8s Mastery: Deep expertise in containerization and deploying high-performance, GPU-enabled Google Kubernetes Engine (GKE) clusters on GCP. 
2️⃣ MLOps Platform Design: Proven track record of architecting scalable MLOps pipelines to support massive AI/ML model training, testing, and production deployment.
 3️⃣ NVIDIA Acceleration Stack: Strong hands-on knowledge of the NVIDIA ecosystem, including CUDA, TensorRT, Triton Inference Server, and NVIDIA NIM to optimize model latency and throughput. 4️⃣ AI Services Integration: Practical experience working with Vertex AI and cloud-native AI/ML services. 
5️⃣ Cross-functional Leadership: Strong communication skills (English B2 or higher) to confidently align with DevOps, ML, and engineering teams on deployment standards.
 

Project Details:
 📍 Location: Remote. 
⏳ Duration: 6–8 months (Full-time allocation). 
🚀 Start: Within 2–3 weeks.