Job Title: DevOps Engineer (Agentic AI) Location: Remote - India
Employment Type: Full-time
Experience: Mid-Level to Senior-Level
bout the Role We are seeking a skilled DevOps Engineer with a strong interest in Agentic AI and Generative AI systems. In this role, you will design, automate, and manage cloud-native infrastructure that powers AI applications, intelligent agents, and large-scale data processing workloads. You will play a key role in building reliable, scalable, and secure platforms for deploying AI-powered products in production environments.
Key Responsibilities - Design, implement, and maintain cloud infrastructure across AWS, Azure, or GCP environments.
- Build and manage CI/CD pipelines for rapid and reliable software delivery.
- utomate infrastructure provisioning and configuration using Infrastructure as Code (IaC) tools.
- Deploy, monitor, and optimize AI/ML and Agentic AI workloads in production environments.
- Manage containerized applications using Docker and Kubernetes.
- Implement observability solutions including logging, monitoring, alerting, and performance tracking.
- Ensure platform reliability, security, scalability, and cost optimization.
- Collaborate closely with software engineers, AI engineers, and product teams to streamline deployment workflows.
- Support MLOps and LLMOps practices for model deployment, evaluation, and lifecycle management.
- Troubleshoot infrastructure, networking, and deployment issues across distributed systems.
Required Qualifications - Strong experience in DevOps, Platform Engineering, or Site Reliability Engineering.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
- Proficiency with Infrastructure as Code tools such as Terraform or CloudFormation.
- Experience building and managing CI/CD pipelines.
- Strong knowledge of Docker, Kubernetes, and container orchestration.
- Proficiency in Python, Shell scripting, or similar automation languages.
- Understanding of networking, cloud security, load balancing, DNS, VPNs, and firewalls.
- Experience with monitoring and observability tools.
- Strong troubleshooting and problem-solving skills.
- bility to thrive in a fast-paced startup environment.
Preferred Qualifications - Experience with MLOps and AI infrastructure.
- Familiarity with Vertex AI, SageMaker, or similar AI/ML deployment platforms.
- Knowledge of Large Language Models (LLMs), Agentic AI systems, and AI orchestration frameworks.
- Experience deploying Retrieval-Augmented Generation (RAG) pipelines and AI-powered services.
- Familiarity with vector databases, distributed systems, and scalable data platforms.
- Exposure to security automation, compliance, and cloud governance practices.
Desired Traits - Passion for emerging AI technologies and intelligent automation.
- Strong ownership mindset and ability to work independently.
- Excellent communication and collaboration skills.
- Continuous learner with a focus on automation, efficiency, and operational excellence.
- Comfortable working in highly dynamic and rapidly evolving environments.
What You'll Gain - Opportunity to build and operate infrastructure for cutting-edge Agentic AI applications.
- Exposure to modern cloud-native technologies, AI platforms, and automation frameworks.
- Remote-first work environment with flexibility and autonomy.
- Collaborative culture focused on innovation, ownership, and continuous learning.
- Significant opportunities for technical growth and leadership as AI adoption scales.
