AI Software Development Lifecycle Lead Engineer - T Cloud Public (REF5733O)

Mission

Lead AI-assisted software engineering activities for Meridian by designing repeatable SDLC patterns that help analyse, validate, document, and evolve complex cloud software stacks. The role anchors the engineering approach for OpenStack-derived services, repository-scale understanding, and sovereign software handover readiness.

Role focus

This senior position focuses on turning AI development platforms into disciplined engineering capability. The candidate should guide how coding agents, open-source or open-weight coding models, and enterprise-approved toolchains are used to accelerate code understanding, refactoring support, documentation, and transition readiness without weakening evidence quality or confidentiality.

Key responsibilities

• Define and lead AI-assisted SDLC patterns for repository intake, code exploration, service mapping, build diagnosis, documentation, and engineering evidence generation.
• Guide analysis of OpenStack-derived control-plane services, APIs, dependencies, integration flows, and build structures across multiple repositories and teams.
• Evaluate and operationalize AI development platforms, coding agents, and approved open-weight or Chinese coding model stacks for secure enterprise use cases.
• Establish human-in-the-loop controls, quality gates, prompt libraries, reusable review patterns, and evidence standards for AI-generated engineering outputs.
• Coach software engineers and platform specialists on safe, effective use of AI tools while coordinating with architecture, security, DevOps, and testing teams.
• Produce senior stakeholder-ready artefacts including transition risks, service decomposition views, codebase maturity observations, and recommended engineering actions.

Examples of market tools, models, and SDLC platforms expected

• AI development environments such as Cursor, Windsurf, Claude Code, Continue, Cline, or VS Code-based extensions connected to enterprise-approved model endpoints.
• Open-source, open-weight, or Chinese coding-capable models such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or similar models operated through approved controls.
• Agentic and SDLC workflow components such as LangGraph, OpenAI Agents SDK, AutoGen, LlamaIndex, RAG pipelines, evaluation loops, and structured tool-calling patterns.
• Engineering environments including GitHub Enterprise, GitLab, Jenkins, ArgoCD, Helm, Docker, Kubernetes, private package registries, and terminal-native automation workflows.

Candidate profile

• 8+ years in software engineering, platform engineering, or technical architecture roles, with proven ownership of complex engineering workstreams.
• Strong hands-on coding skills in Python plus at least one backend or systems language such as Go, Java, C, C++, or Rust.
• Deep practical experience using AI coding agents and LLM-enabled SDLC workflows for large codebases, technical documentation, and engineering acceleration.
• Good understanding of OpenStack-derived cloud software architectures, modular service decomposition, CI/CD, Kubernetes-based delivery, and platform operations.
• Able to lead senior engineers in ambiguous environments, challenge AI outputs, and convert incomplete evidence into structured, actionable engineering decisions.
• Comfortable working in high-accountability, confidentiality-sensitive enterprise programs where auditability, traceability, and sovereignty constraints are mandatory.

Please note

remote working is only possible from within Hungary due to European taxation regulations.

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