Agentic AI Solutions Engineer

External

Suse · Emea, Czechia

Full-timeOn-siteToday

AirflowConfluenceDocumentationExcelJiraKubernetes

Cover Letter Connect

Prepare for this interview

Elite

AI-generated questions, company research, and talking points tailored to this role

About the role

Always open. Our code, our culture, our opportunities. Leading open innovation without limits. We are SUSE. SUSE is a global leader in innovative, reliable, and secure enterprise open source solutions, including SUSE® Linux Suite , SUSE® Rancher Suite , SUSE® Edge Suite , and SUSE® AI Suite . More than 60% of the Fortune 500 rely on SUSE to power their mission-critical workloads, enabling them to innovate everywhere - from the data center to the cloud, to the edge and beyond. SUSE puts the "open" back in open source, collaborating with partners and communities to give customers the agility to tackle innovation challenges today and the freedom to evolve their strategy and solutions tomorrow. For more information, visit www.suse.com . Agentic AI Solutions Engineer Job Description SUSE is building a highly secure, sovereign Agentic AI platform to automate enterprise workflows and pioneer the "Agent Factory" model. We are looking for a Senior Fullstack Engineer to join our IT Strategy function. In this role, you will be the bridge between technical complexity and business utility, sitting directly between our Solution Architect and Platform Infrastructure Engineer. You will own the application layer of our "Agent Factory," specifically focused on building the agentic solutions and workflows that employees need to excel in their everyday jobs. You will be designing "digital teammates" and "Utility Agents" that handle the repetitive, complex, or data-heavy tasks that comprise our future workforce's daily life. You understand that AI is a systems engineering challenge, not just a prompt engineering task. You will have the autonomy to select and deploy the right modern, open-source tools to orchestrate agentic workflows, integrate internal Systems of Record with Sovereign LLMs, and build the interfaces that power our Human-in-the-Loop (HITL) architecture.

Responsibilities

Building Everyday Agentic Solutions

Design Practical Assistants: Architect and build agents that directly assist business users in their daily tasks, such as automating complex data retrieval, summarizing cross-departmental reports, or triaging internal requests.

Workflow Orchestration: Design and build agentic and multi-agentic workflows using modern orchestration engines (e.g., n8n, Temporal, LangGraph, Airflow), wiring legacy internal APIs to both Sovereign Local LLMs and External Commodity LLMs to solve real-world business friction.

Utility Agent Creation: Develop core "Utility Agents" - and, over time, creating a library of digital skills that business units can draw upon.

Standardization: Define and document integration patterns and standardized inputs/outputs to ensure agents can be "plugged in" to various business workflows with modular scalability.

Custom Tooling & Backend Engineering

Microservices Mastery: Write highly performant microservices and custom orchestrator plugins using modern backend languages (Python, TypeScript, Go) to handle complex enterprise data.

Resiliency & Guardrails: Code robust error-handling, exponential backoff, and fallback routing to ensure API rate limits or LLM hallucinations do not break production systems used by the business daily.

Deployment: Work within containerized environments (Linux/Kubernetes) to ensure secure, cloud-native deployments of AI solutions.

Human-in-the-Loop (HITL) & Frontend

Dashboard Development: Build lightweight, secure frontend dashboards where business managers can review, approve, or reject high-risk actions proposed by autonomous agents.

User Interface: Quickly spin up clean, functional internal tooling and approval interfaces using modern frameworks (React, Vue, or Svelte) that integrate seamlessly into the user's existing workspace.

Data Engineering & RAG Pipelines

Robust Data Ingestion: Design pipelines connecting disparate internal data sources (e.g. Confluence, Jira, PDFs) to Vector Databases to ensure agents have the context they need to assist employees accurately.

Retrieval Optimization: Optimize chunking, embedding, and retrieval strategies to minimize noise and maximize the accuracy of RAG-based systems.

Enablement & Strategy

AGENT Framework Execution: Follow the "Assess, Govern, Engineer, Network, Transform" framework to transition the organization from bespoke experiments to an industrialized factory model.

Business Enablement: Collaborate directly with business stakeholders to identify tasks that can be automated, creating training materials/documentation to enable users to leverage their new digital assistants.

What We Are Looking For (Hard Skills)

Backend Proficiency: Deep experience in modern backend languages (Python is required; TypeScript or Go is highly desirable).

AI/LLM Ecosystem: Proven hands-on experience with LLM APIs and agentic frameworks (e.g., LangChain, LlamaIndex, ReAct patterns).

Workflow Orchestration: Experience with programmatic or visual tools (n8n experience is a major plus).

Vector &

Agentic AI Solutions Engineer

About the role

Responsibilities

Your Match

Company Intel

What employees say

Interested in this role?