Agentic AI & ITSM/AIOps Solutions Architect

T-Systems Iberia

HybridPosted July 29, 2026

About the role

Agentic AI & ITSM/AIOps Solutions Architect – a senior role to design enterprise solutions based on generative AI, intelligent agents, retrieval-augmented generation (RAG), automation, observability and workflow orchestration, with a focus on support, operations, ITSM, AIOps and service management.

Responsibilities

Agentic AI & ITSM/AIOps Solutions Architect

T-Systems Iberia

HybridPosted July 29, 2026

About the role

Agentic AI & ITSM/AIOps Solutions Architect – a senior role to design enterprise solutions based on generative AI, intelligent agents, retrieval-augmented generation (RAG), automation, observability and workflow orchestration, with a focus on support, operations, ITSM, AIOps and service management.

Responsibilities

Design generative AI solutions applied to business and operational processes.
Define agentic architectures: agents, subagents, tools, memory, context, workflows and control points.
Create AI workflows for ITSM/AIOps: classification, prioritization, assignment, diagnosis, resolution, escalation, closure, reopen, and continuous learning.
Define RAG patterns across documentation, knowledge bases, tickets, runbooks, logs, metrics and traces.
Develop advanced prompting strategies, structured generation, evidence retrieval and evaluation of responses.
Define scoring models: confidence, similarity, risk, criticality, automation eligibility and answer quality.
Establish human-in-the-loop mechanisms, policy gates and criteria to differentiate between assisted, supervised or autonomous automation.
Integrate AI agents with APIs, internal systems, cloud platforms, ITSM tools, observability tools, external services and corporate data sources.
Identify automation candidates from process analysis and operational history.
Contribute to service development and deployment using automated code generation tools.
Coordinate and support technical teams implementing AI agent-based solutions, RAG, workflows and automation.
Drive continuous improvement of agents

Design generative AI solutions applied to business and operational processes.
Define agentic architectures: agents, subagents, tools, memory, context, workflows and control points.
Create AI workflows for ITSM/AIOps: classification, prioritization, assignment, diagnosis, resolution, escalation, closure, reopen, and continuous learning.
Define RAG patterns across documentation, knowledge bases, tickets, runbooks, logs, metrics and traces.
Develop advanced prompting strategies, structured generation, evidence retrieval and evaluation of responses.
Define scoring models: confidence, similarity, risk, criticality, automation eligibility and answer quality.
Establish human-in-the-loop mechanisms, policy gates and criteria to differentiate between assisted, supervised or autonomous automation.
Integrate AI agents with APIs, internal systems, cloud platforms, ITSM tools, observability tools, external services and corporate data sources.
Identify automation candidates from process analysis and operational history.
Contribute to service development and deployment using automated code generation tools.
Coordinate and support technical teams implementing AI agent-based solutions, RAG, workflows and automation.
Drive continuous improvement of agents

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