Agentic AI DevOps Specialist

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The role is expected to be able to develop, deploy, maintain, operate and support an Agentic AI Developer Platform that would serve the whole client’s company and centralize all the agentic developments under its orbit.

The role is expected to complement and work side by side with the Technical Lead of the team, providing the most specialized knowledge and hand on experience to the team, complementing the Technical Lead at guiding the team to a successful implementation of the platform and to its long term sustainability.

The platform won’t be necessarily internally developed, it may well be composed by an orchestration of already existing software platforms and/or frameworks, along with some degree of customization and abstraction aimed at providing agentic developers of the company with a tailored experience that aligns with the company standards.

To be able to perform this responsibilities as expected by the client, the candidate must fulfil two important requirements that are broad areas of knowledge and hands-on implementation experience:

DevOps experience with a focus on Kubernetes

Agentic AI experience, with a focus on lifecycle platforms (e.g. LangFuse)

Regarding DevOps skills, the candidate is expected to have at least 4 years of job experience in roles such as DevOps and/or backend engineer. Additionally, the candidate is expected to possess areas of knowledge that are broadly related to the topics listed below. It is not required that the candidate has experience or knowledge on all of the listed topics, or on any one in particular, the list is intended to be just a guideline of the kinds of things we are looking for:

General knowledge of Linux OS administration

General knowledge of containers, images and container registries

Concepts of IAM and RBAC

Internal Development Platforms (IDP), self-service infrastructure, golden paths

General knowledge of IaC concepts and hands on experience with Terraform

General knowledge Kubernetes, its entities and networking with hands on experience

Kubernetes administration, helm charts and automations

Standardizations of development processes

Templates and scaffolding for development on Kubernetes

Design, implementation and operation of CI/CD pipelines and related frameworks

GitHub actions or similar frameworks

CI/CD frameworks on Kubernetes

Monitoring and observability on Kubernetes

ML frameworks for Kubernetes (Kserve, Kubeflow, Ray, etc)

Regarding Agentic AI skills, the candidate is expected to have at least 1 to 2 years of job experience in related roles. Additionally, the candidate is expected to possess areas of knowledge that are broadly related to the topics listed below. It is not required that the candidate has experience or knowledge on all of the listed topics, or on any one in particular, the list is intended to be just a guideline of the kinds of things we are looking for:

General knowledge of commercial and open source LLMs and their trade offs

Prompt engineering

Prompt templating, versioning, A/B testing and management

Prompt guardrails design and implementation, prompt injection defense

Agentic skills specification and best practices

Agentic orchestration frameworks (LangChain, LangGraph, etc)

Autonomous agent architectures

Frameworks for monitoring, tracing,debugging and evaluating agentic flows (LangSmith, LangFuse, etc)

General knowledge of text embedding models

Vector databases, semantic search, RAG

Cost optimization of prompts and agentic pipelines

External memory layer and tools

MCP frameworks