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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying AI agents and multi-agent systems using Azure AI services, with a strong focus on LLM application development, agentic frameworks, and enterprise RAG solutions. Proficient in integrating AI solutions with Microsoft 365 and optimizing applications for performance and security.
Highest-signal resume keywords
Azure AI ServicesAgentic FrameworksLLM Application DevelopmentPython ProgrammingAI Security and Governance
ATS Keywords
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Hard Skills
AI Application DevelopmentEnterprise RAG ArchitecturesVector Search TechnologiesPrompt EngineeringMachine Learning FrameworksWorkflow OrchestrationModel EvaluationObservability ToolsIntegration with Microsoft 365Azure OpenAI
Soft Skills
CollaborationProblem-SolvingUser Feedback Iteration
Tools & Technologies
KubeFlowBentoMLEvidently AIGreat ExpectationsAzure AI Foundry
Certifications & Qualifications
Machine Learning CertificationData Science CertificationStatistical Analysis Certification
Industry Keywords
AI AgentsMulti-Agent SystemsAI WorkflowsEnterprise APIsAI Engineering Standards
Tech Stack
Tools & technologiesAzureKerasPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design, build, and deploy AI agents and multi-agent systems using Azure AI services, Azure OpenAI, and agentic frameworks
- Develop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs
- Implement enterprise RAG solutions using Azure AI Search, vector search, hybrid search, and semantic ranking
- Build production-ready AI applications leveraging LLMs, RAG pipelines, tool/function calling, memory systems, and workflow orchestration
- Establish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for production AI applications
- Optimize agent and LLM applications for latency, accuracy, reliability, scalability, security, and cost
- Collaborate with cross-functional teams to identify AI opportunities, rapidly prototype solutions, and iterate based on user feedback
- Contribute to internal best practices around agent architecture, prompting, RAG, model selection, evaluation, and AI engineering standards
Requirements
What you’ll need- With at least 4 to 6 years of experience designing, building, and operationalizing enterprise-scale AI platforms, including hands-on expertise in agentic AI, LLMs, and Azure-based solutions
- Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry
- Expertise in agentic frameworks: Semantic Kernel, LangChain, LangGraph, and AutoGen
- LLM application development and prompt engineering
- Enterprise RAG architectures and vector search technologies
- Integration with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs
- Python programming for AI/ML solutions
- Experience with ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, and Keras
- Experience with AI workflow orchestration tools: KubeFlow and BentoML
- Experience with model evaluation and observability tools: Evidently AI and Great Expectations
- AI security and governance on Azure
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline is desired
- Certification in Machine Learning or Data Science from a recognized institution is desired
- Certification in statistical analysis tools or platforms is desired