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We are seeking a DevOps Technical Lead with a strong background in infrastructure automation, cloud architecture, and a keen interest in Generative AI technologies. The ideal candidate will lead the development of an Infrastructure Agent powered by GenAI – capable of intelligent provisioning, configuration, observability, and self-healing.
Job Responsibility:
Lead architecture & design of an intelligent Infra Agent leveraging GenAI capabilities
Integrate LLMs and automation frameworks (e.g., LangChain, OpenAI, Hugging Face) to enhance DevOps workflows
Build solutions that automate infrastructure provisioning, CI/CD, incident remediation, and drift detection
Develop reusable components and frameworks using IaC (Terraform, Pulumi, CloudFormation) and configuration management tools (Ansible, Chef, etc.)
Partner with AI/ML engineers and SREs to design intelligent infrastructure decision-making logic
Implement secure and scalable infrastructure on cloud platforms (AWS, Azure, GCP)
Continuously improve agent performance through feedback loops, telemetry, and fine-tuning of models
Drive DevSecOps best practices, compliance, and observability
Mentor DevOps engineers and collaborate with cross-functional teams (AI/ML, Platform, and Product)
Requirements:
Bachelor's or Master’s degree in Computer Science, Engineering, or related field
8+ years of experience in DevOps, SRE, or Infrastructure Engineering
Proven experience in leading infrastructure automation projects and technical teams
Expertise with one or more cloud platforms: AWS, Azure, GCP
Deep knowledge of tools like Terraform, Kubernetes, Helm, Docker, Jenkins, and GitOps
Hands-on experience integrating or building with LLMs / GenAI APIs (e.g., OpenAI, Anthropic, Cohere)
Familiarity with LangChain, AutoGen, or custom agent frameworks
Experience with programming/scripting languages: Python, Go, or Bash
Understanding of cloud security, policy as code, and monitoring tools (Prometheus, Grafana, Datadog)
Nice to have:
Experience building or fine-tuning LLM-based agents for operations or automation tasks
Contributions to open-source GenAI or DevOps projects
Understanding of MLOps pipelines and AI infrastructure
Certifications in DevOps, cloud, or AI technologies (e.g., AWS DevOps Engineer, Azure AI Engineer)