Azure AI/ML Engineer

Years of Exp: 5 to 10 years

5–8 years of experience in software engineering or AI/ML development, with at least 4+ years working with Azure AI services.

Strong hands-on experience with Python for backend development, AI pipelines, and LLM integrations.

Strong hands-on experience with Azure AI Document Intelligence including extraction, forms, OCR, and classification.

Deep understanding of Azure OpenAI, including GPT models, embeddings, chat completions, prompt engineering, and content safety.

Practical experience using Azure AI Foundry for building, testing, and operationalizing AI apps.

building AI solutions in cloud-native Azure environments including:

Hands-on experience making calls to LLM APIs (chat completions, embeddings, model inference endpoints) and integrating them into applications.

architecting and implementing RAG systems using Azure Cognitive Search or vector index stores.

Strong programming experience in Python or C# (Node.js acceptable) for backend microservices and integrations.

Practical experience with Azure services including Logic Apps, Event Grid, Storage, Functions, and automated workflows.

Solid knowledge of Responsible AI, privacy, compliance, and secure deployment models.

Strong debugging and optimization skills for AI workloads (cost, latency, throughput).

Hands-on experience with Azure DevOps, Git repositories, CI/CD pipelines, IaC, and deployment automation.

Strong analytical, communication, and stakeholder management skills.

Experience using vector databases such as Azure Cosmos DB with vector indexing, Redis Enterprise, or Pinecone.

Familiarity with multi-agent AI architectures, orchestration frameworks, and agentic workflows.

Exposure to Power Platform AI Builder and low-code AI integrations.

Understanding of NLP techniques including entity extraction, embeddings, semantic search, text analytics, and conversation design.

with frameworks like LangChain, Semantic Kernel, or LlamaIndex.

Certifications such as: