Shape the Infrastructure Behind Enterprise AI 🚀
AI is no longer experimental - it is mission-critical. As global organizations move toward autonomous AI agents operating on sensitive data, they need secure, scalable, and compliant platforms.
This is where you come in.
🟢 We are looking for a Manager / Senior Lead in DevOps & LLMOps to design and lead the deployment of enterprise-grade Agentic AI platforms. You will help some of the world’s most recognized organizations build secure AI environments that operate at scale — and under strict regulatory standards.
If you are excited about combining deep engineering with high-impact consulting, this role offers exactly that.
💼 Your Profile
We are looking for a technically strong leader who is comfortable operating in complex environments.
Core Experience
4–8+ years in Cloud Engineering, DevOps, or SRE
Proven experience delivering complex projects in Azure (preferred), AWS, or GCP
Strong Kubernetes expertise (Helm, Kustomize)
CI/CD automation (GitHub Actions, Azure DevOps)
Security & Compliance Mindset
Identity & access management
Encryption (at rest and in transit)
Understanding of SOC2 / ISO-level compliance standards
Nice to Have
Experience with Vector Databases (Milvus, Pinecone)
GPU workload scheduling
Scaling workflow engines (e.g., n8n)
Exposure to LLMOps or GenAI production environments
AI is no longer experimental - it is mission-critical. As global organizations move toward autonomous AI agents operating on sensitive data, they need secure, scalable, and compliant platforms.
This is where you come in.
🟢 We are looking for a Manager / Senior Lead in DevOps & LLMOps to design and lead the deployment of enterprise-grade Agentic AI platforms. You will help some of the world’s most recognized organizations build secure AI environments that operate at scale — and under strict regulatory standards.
If you are excited about combining deep engineering with high-impact consulting, this role offers exactly that.
💼 Your Profile
We are looking for a technically strong leader who is comfortable operating in complex environments.
Core Experience
4–8+ years in Cloud Engineering, DevOps, or SRE
Proven experience delivering complex projects in Azure (preferred), AWS, or GCP
Strong Kubernetes expertise (Helm, Kustomize)
CI/CD automation (GitHub Actions, Azure DevOps)
Security & Compliance Mindset
Identity & access management
Encryption (at rest and in transit)
Understanding of SOC2 / ISO-level compliance standards
Nice to Have
Experience with Vector Databases (Milvus, Pinecone)
GPU workload scheduling
Scaling workflow engines (e.g., n8n)
Exposure to LLMOps or GenAI production environments