AI SWE / Agentic Handover Engineer - T Cloud Public (REF5673M)

Mission

Deliver AI-assisted handover and due diligence support with added emphasis on automation, repeatability, evidence generation, and reusable workflow packaging across multiple engineering work packages. A central goal of the role is to create repeatable AI-assisted workflows that help assess, document, and transition a cloud software stack derived from OpenStack.

Role focus

This second position complements Position A by emphasizing workflow engineering so that AI-assisted code understanding can be reused consistently across repositories, teams, and technical assessment tasks. The role should help industrialize analysis of modular cloud software environments based on OpenStack-style architecture and related CI/CD and integration flows.

Key responsibilities

• Build reusable AI-assisted workflows for repository intake, code scanning, dependency extraction, build issue triage, and documentation generation.
• Package prompts, retrieval steps, tool integrations, and evaluation logic into repeatable engineering patterns suitable for enterprise delivery.
• Create workflow accelerators that support the analysis and handover of a cloud software stack derived from OpenStack, including service mapping, control-plane understanding, and cross-component dependency views.
• Help define quality gates for AI-assisted outputs, including traceability, explainability, approval points, and human-in-the-loop controls.
• Partner with technical PMO and work-package leads to produce evidence packs that support decisions, risks, and transition readiness views.
• Improve throughput of technical due diligence activities without compromising engineering quality, auditability, or confidentiality constraints.[

Examples of market tools and workflow frameworks expected

• Agentic workflow frameworks such as LangGraph, OpenAI Agents SDK, AutoGen, CrewAI, LlamaIndex Workflows, or similar orchestration stacks.
• Tool integration and agent control patterns such as memory, tool calling, structured retries, fallback logic, evaluation loops, and human-in-the-loop review stages.
• Supporting components such as vector databases, retrieval layers, observability tooling, and API/service wrappers that allow workflows to operate across code, documents, and engineering evidence.
• Engineering workflows that can operate across OpenStack-related repositories, CI/CD systems, architecture metadata, test outputs, and service dependency graphs are especially relevant.

Candidate profile

• 5+ years of engineering experience with strong delivery discipline and comfort operating across software, DevOps, and documentation boundaries.
• Hands-on background in Python, APIs, orchestration frameworks, and developer tooling.
• Practical experience with AI systems in production, especially RAG, evaluation pipelines, tool use, prompt workflows, and observability.
• Strong written communication skills for producing concise engineering evidence and handover outputs for senior stakeholders.
• Ability to work in ambiguous environments and translate partial technical evidence into structured findings and recommendations.
• Familiarity with modular cloud software stacks derived from OpenStack, or similarly complex multi-service infrastructure platforms, is strongly preferred.

You will be working in the European Union to meet our customers' data security and privacy requirements.

• Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.