Senior Azure GenAI/ML Engineer

Job description
We are seeking a highly skilled Azure AI / ML Engineer to design, develop, and deploy advanced AI solutions on Microsoft Azure.
In this role, you will work closely with other AI engineers, software developers, and product stakeholders to build scalable, secure, and high-performance AI systems that drive business outcomes. Success in this position looks like performing rapid proof-of-concepts, moving successful outcomes to an MVP, then delivering production-ready AI solutions that improve decision-making, automate complex tasks, and generate measurable impact for the organization. If you have a Microsoft Full-Stack development experience, this will be a huge plus.
This role is critical to advancing our AI strategy and integrating cutting-edge technology into our products and services.
Responsibilities
Design, develop, and deploy machine learning models using Azure Machine Learning (Azure ML), Azure OpenAI, Gemini and related services
Build and maintain scalable data pipelines to prepare data for AI / ML models, using tools like Azure Data Factory and MS Fabric
Collaborate with product teams to translate business requirements into AI / ML solutions that deliver clear value
Optimize model performance, monitor drift, and manage the lifecycle of AI models in production
Implement responsible AI practices including fairness, explainability, and compliance with ethical guidelines
Automate model training, testing, and deployment workflows using Azure DevOps and MLOps practices
Stay current with advances in Azure AI services, generative AI, LLMs, and emerging trends to recommend innovative solutions
Document technical designs, workflows, and best practices to enable knowledge sharing across the team
Follow standard DevOps practices with ADO and Github
Qualifications
Skills:
Strong programming skills in Python and C# .NET
Proficiency with Azure ML, Azure OpenAI, Azure AI Search, and AI Foundry
Strong experience with LLMs, RAG, AI Agents, vector db, embeddings, LangChain, Semantic Kernel
Experience with MLOps tools such as Azure DevOps, GitHub Actions, or MLflow
Strong understanding of machine learning algorithms, deep learning, and statistical modeling
Excellent problem-solving and communication skills
Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
Experience:
3+ years of experience developing and deploying AI / ML solutions, with at least 2 years on Azure
Experience working in agile teams and collaborating cross-functionally
Sorry we're unable to hire students or recent graduates
Certifications (preferred but not required):
Microsoft Certified: Azure AI Engineer Associate
Microsoft Certified: Azure Data Scientist Associate
Industry
IT Services and IT Consulting
Employment Type
Full-time / Remote

Work arrangement
Yes