DevOps Engineer (Agentic AI)

Job Title: DevOps Engineer (Agentic AI)
Location: Remote India
Employment Type: Full-time
Experience: Mid-Level to Senior-Level

About 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.
• Automate 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.
• Ability 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.