AI Architect – Generative AI & Machine Learning

About the role

We are seeking a hands‑on AI Architect with deep expertise in Generative AI and Machine Learning to lead the design, development, and production deployment of AI solutions. The role combines technical execution with solution architecture, stakeholder engagement, and a strong focus on responsible AI.

Key responsibilities

• Own end‑to‑end delivery of multiple GenAI and ML projects, from requirement gathering to production deployment.
• Define solution architecture and design decisions ensuring scalability, security, and performance.
• Engage business and client stakeholders to translate needs into practical AI solutions.
• Build APIs, integrate Azure AI services, and troubleshoot production issues.
• Design and implement Retrieval‑Augmented Generation (RAG) pipelines using Azure AI Search with vector, semantic, and hybrid retrieval.
• Develop LLM‑powered applications on Azure OpenAI, applying advanced prompt engineering and structured output techniques.
• Implement human‑in‑the‑loop workflows, red‑teaming, and guardrails for bias mitigation and compliance.
• Set up observability, tracing, and monitoring using tools such as Langfuse, LangSmith, or Azure AI Foundry.
• Deploy solutions on Azure with CI/CD pipelines, logging, and full audit trails.
• Mentor junior engineers and ensure overall solution quality.

Required profile

• 8+ years of experience in AI/ML engineering and solution architecture.
• 3+ years of hands‑on experience delivering GenAI and LLM‑based applications in production.
• Proven track record leading multiple enterprise AI projects with direct stakeholder interaction.
• Strong understanding of RAG architectures, embeddings, vector databases, and LLM orchestration.

Required skills

• Azure AI Search
• Azure OpenAI
• LangGraph, AutoGen, Semantic Kernel, CrewAI
• Langfuse, LangSmith, Azure AI Foundry
• Application Insights and Azure monitoring tools
• CI/CD pipeline implementation
• Prompt engineering and structured output design
• Observability and tracing for AI systems