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.