23 hours ago
Madrid, SpainSenior
Responsibilities
- Identify operational use cases for Generative AI and Agentic AI and turn them into production architectures.
- Design AI agents and intelligent workflows for incident detection, investigation, resolution, root-cause analysis, observability, capacity management, knowledge management, change management, remediation, and infrastructure lifecycle activities.
- Integrate AI capabilities with observability, ITSM, Kubernetes, cloud and on-premises infrastructure, CI/CD, infrastructure-as-code, configuration data, operational data, and orchestration platforms.
- Define secure, auditable, identity-aware access for AI agents to enterprise tools, data, and operational systems.
- Develop reusable architectures for agentic AI, AI orchestration, enterprise AI platforms, model access, RAG, tool/API integration, model and agent observability, evaluation, governance, and hybrid-cloud AI.
- Help platform engineering teams implement reusable services, Kubernetes architectures, GitOps approaches, self-service capabilities, platform APIs, golden paths, and reliability patterns.
- Ensure AI solutions meet production requirements for reliability, scalability, security, observability, maintainability, cost efficiency, human oversight, responsible AI, and operational support.
- Work with senior stakeholders and engineers to review architectures, diagnose limitations, and contribute to prototypes when necessary.
Requirements
- Strong architecture experience in large enterprise IT environments.
- Experience in Platform Engineering and/or SRE, cloud-native and hybrid-cloud architecture, infrastructure as code, CI/CD and DevSecOps, observability, APIs and integration, automation and orchestration, and production IT operations.
- Experience with Kubernetes platforms such as AKS or OpenShift.
- Hands-on understanding of modern AI architectures, including Generative AI or large language models, Agentic AI, agent orchestration, RAG, tool calling, evaluation, prompt and context engineering, AI observability, guardrails, responsible AI, model gateways, or enterprise model access.
- Experience with Azure AI Foundry, Azure OpenAI, Google Vertex AI, LangGraph, or equivalent frameworks is valuable.
- Ability to discuss implementation decisions with engineers, review architectures and prototypes, understand APIs, Kubernetes workloads, CI/CD pipelines, infrastructure as code, and operational limitations.
- Senior technology architect profile with an engineering mindset and the ability to work across CTO-level discussions and detailed engineering sessions.
Benefits
- Hybrid-friendly work culture with programs supporting financial, mental, physical, and social well-being.
- Career development support including personalized development goals, continuous feedback, certifications with Microsoft, Google, and Amazon, coaching, and hands-on learning opportunities.
- Inclusive culture focused on belonging, empathy, professional growth, and shared success.
Tech Stack
Categories
About Kyndryl
Kyndryl is a public IT services company that designs, runs, and modernizes mission-critical infrastructure for large enterprises and governments. Spun off from IBM in 2021, it is headquartered in New York City and trades on the NYSE (ticker: KD). The company provides managed infrastructure, cloud migration and operations across AWS, Azure, and Google Cloud, plus mainframe, network, security, data, and digital workplace services.