Senior Artificial Intelligence Engineer

Role & responsibilities

• 5+ years of in AI and overall IT / software engineering experience.
• 3+ years of hands-on application development experience.
• 3+ years of Python and API development preferred.
• 2 years of Microsoft Azure cloud engineering preferred.
• 2 years of practical Azure OpenAI project experience preferred.
• Demonstrated production or near-production implementation experience with RAG / enterprise knowledge solutions.
• Strong hands-on expertise in Python, SQL, REST APIs, JSON, asynchronous programming, object-oriented design, and unit testing.
• Strong hands-on expertise in Azure OpenAI, GPT models, embeddings, prompt engineering, structured output, function calling, and AI agents.
• Hands-on experience with Azure AI Search, vector indexing, semantic and hybrid search, chunking, retrieval, reranking, and grounding.
• Hands-on experience with Semantic Kernel, Lang Chain, Llama Index, AutoGen or comparable orchestration frameworks.
• Strong Azure platform experience across Azure AI Foundry, Functions, App Service, Storage, Key Vault, SQL, Cosmos DB, Monitor, Container Apps / AKS.
• Strong understanding of microservices, event-driven design, API security, integration patterns, scalability, and resiliency.
• Experience with Git, Azure DevOps or GitHub, CI/CD, Docker, and Kubernetes; Infrastructure as Code preferred.
• Experience with Microsoft Entra ID, RBAC, managed identity, network isolation, secrets, Responsible AI, and audit controls.
• Hands-on experience with Application Insights, Azure Monitor, logging, tracing, quality evaluation, usage and cost monitoring.
• Strong problem-solving skills and the ability to balance business value, engineering quality, security, cost, and delivery speed.
• Strong communication skills with the ability to explain complex AI architecture and risks to technical and non-technical stakeholders.
• Practical ownership mindset, with evidence of taking AI solutions from design through production operations.

Preferred candidate profile

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or a related discipline.
• Microsoft certification in Azure AI, Azure development, Azure architecture, data engineering, or DevOps.
• Experience delivering enterprise Copilot, intelligent document processing, IT automation, or knowledge management solutions.
• Exposure to manufacturing, automotive, supply chain, quality, finance, or enterprise IT use cases.
• Experience with Infrastructure as Code, model evaluation frameworks, AI red teaming, or production LLM observability.