Why this role matters
Lead the design and deployment of enterprise-grade generative AI solutions on Azure. Your work will drive innovation and deliver measurable value across business functions.
Responsibilities
• Design scalable, secure generative AI architectures using Azure OpenAI Service, Azure ML, Cognitive Services, AKS, and vector databases.
• Define and lead AI adoption strategies aligned with business objectives, focusing on text, image, and code generation use cases.
• Evaluate, integrate, tune, and operationalise foundation models like GPT, DALL·E, and Codex.
• Build automated AI pipelines and MLOps workflows with Azure ML, Data Factory, Synapse, DevOps, and LLM orchestration tools such as LangChain or Semantic Kernel.
• Ensure compliance with responsible AI principles, data governance standards and regulatory requirements.
• Partner with senior leadership to translate technical concepts into clear business recommendations.
• Stay current with generative AI trends and emerging Azure tools; propose new use cases and solutions.
Required experience and skills
• Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML or related field.
• At least seven years of solution architecture experience, including a minimum of two years working hands-on with Azure AI and generative models.
• Expertise in Azure OpenAI Service, Azure ML, Cognitive Search, AKS, and vector databases such as Cosmos DB, Pinecone or Weaviate.
• Practical experience with LLM orchestration frameworks like LangChain or Semantic Kernel, and with prompt engineering and model fine‑tuning.
• Programming proficiency in Python, C# or equivalent, and solid understanding of REST APIs, CI/CD pipelines and DevOps practices.
• Preferred certifications: Microsoft Certified: Azure Solutions Architect Expert and/or Azure AI Engineer Associate.
What's in it for you?
• Competitive base salary with performance-based bonuses.
• Flexible working arrangements to support work-life balance.
• Opportunities to work on leading-edge generative AI projects with visible business impact.
• Access to training, mentoring and support for achieving Azure certifications.
• Collaborative, innovative team culture focused on real-world outcomes.
What sets you apart
Proven ability to deliver tangible results—share past projects where you architected or deployed generative AI solutions, including key metrics and business impact. Demonstrated use of Azure-native tools and best practices in MLOps and responsible AI.
