engineering
Posted Jun 12Agentic AI Solutions Engineer
at SUSE
CzechiaOn-site
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.
- 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.
Requirements
- Agentic AI Solutions Engineer Job Description
- About the Role SUSE is building a highly secure, sovereign Agentic AI platform to automate enterprise workflows and pioneer the "Agent Factory" model.
- 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 understand that AI is a systems engineering challenge, not just a prompt engineering task.
- Utility Agent Creation: Develop core "Utility Agents" — and, over time, creating a library of digital skills that business units can draw upon.
- 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.
- Deployment: Work within containerized environments (Linux/Kubernetes) to ensure secure, cloud-native deployments of AI solutions. 3.
- Confluence, Jira, PDFs) to Vector Databases to ensure agents have the context they need to assist employees accurately.
- 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 with modern Vector Databases (e.g., Milvus, Qdrant, Pinecone) and parsing unstructured data.
- Infrastructure Basics: Comfortable with Linux, Kubernetes (k8s), and REST API design.
- A User-Centric Engineer: You have a passion for understanding how people work and an obsession with building tools that make their "everyday jobs" easier and more impactful.
- A Pragmatic Technologist: You stay at the bleeding edge of the open-source AI community and know when to adopt a new framework versus when to write custom code for security.
- SUSE Values Trust: Ensuring a secure, governed, and reliable Agent Mesh through technical implementation of Responsible AI.
- Choice: Empowering our teams and customers with the flexibility of open standards, ensuring modularity in our AI stack to avoid vendor lock-in.
Contact
- For more information, visit www.suse.com .
Additional details
- Leading open innovation without limits. We are SUSE.
- 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.
- 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 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 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. What You Will Do 1.
- 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.
- Standardization: Define and document integration patterns and standardized inputs/outputs to ensure agents can be "plugged in" to various business workflows with modular scalability. 2.
- 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.
- 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. 4.