Agentic AI DevOps Specialist
New
ArgentinaFull-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 4+ years in DevOps/Platform/SRE/Backend; 1–2+ years in Agentic AI/GenAI/LLM
- Required Skills
- KubernetesCI/CDLinuxTerraformPrompt EngineeringLangChain
Requirements
- 4+ years of experience in DevOps, Platform Engineering, SRE, or Backend Engineering.
- Strong Kubernetes experience, including administration, networking, Helm, and automation.
- Experience with Terraform and Infrastructure as Code.
- Experience designing and maintaining CI/CD pipelines (GitHub Actions or similar).
- Knowledge of Linux administration, containers, registries, IAM, and RBAC.
- Experience with observability, monitoring, and cloud-native infrastructure.
- Familiarity with Internal Developer Platforms (IDPs) and self-service infrastructure concepts.
- 1–2+ years of hands-on experience working with Agentic AI, GenAI, or LLM-based platforms.
- Experience with frameworks such as LangChain, LangGraph, LangFuse, LangSmith, or similar.
- Knowledge of prompt engineering, prompt versioning, evaluation, and A/B testing.
- Experience with RAG architectures, vector databases, embeddings, and semantic search.
- Understanding of agent orchestration patterns, autonomous agents, and tool integrations.
- Familiarity with MCP, memory layers, guardrails, and AI observability practices.
- Understanding of commercial and open-source LLMs and their trade-offs.
Responsibilities
- Design, deploy, maintain, and operate an enterprise Agentic AI Developer Platform.
- Build and manage Kubernetes-based infrastructure supporting AI and agentic workloads.
- Develop Infrastructure as Code (IaC) solutions using Terraform and related tooling.
- Design and maintain CI/CD pipelines, automation frameworks, and deployment processes.
- Implement observability, monitoring, tracing, and operational best practices.
- Evaluate, integrate, and customize AI platforms, frameworks, and developer tooling.
- Enable self-service development experiences through templates, scaffolding, and standardized workflows.
- Support prompt lifecycle management, agent orchestration, and AI platform governance.
- Collaborate with technical stakeholders to ensure scalability, security, reliability, and cost efficiency.
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