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AI Engineer – Agentic AI, Cloud Infrastructure
iSupport Worldwide. Design, develop, and deploy AI agents capable of performing multi-step tasks and automating business workflows .
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 intelligent automation systems, with strong proficiency in Python and hands-on experience with Microsoft Azure and related tools. Capable of optimizing workflows, integrating enterprise systems, and delivering training sessions to clients.
Highest-signal resume keywords
Python ProgrammingMicrosoft AzureAI Agent DevelopmentCI/CD PipelinesModel Fine-Tuning
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI EngineeringMachine Learning EngineeringBackend Services DevelopmentREST APIsTool CallingLLM OrchestrationModel EvaluationInference OptimizationDatabase ManagementSecurity Implementations
Soft Skills
Client CommunicationKnowledge TransferProblem Solving
Tools & Technologies
Microsoft FoundryAzure AI Agent ServiceLangGraphSemantic KernelAzure DevOpsGitTerraformBicepMicrosoft TeamsMicrosoft Graph API
Industry Keywords
AI AgentsIntelligent AutomationMulti-Agent WorkflowsEnterprise System IntegrationOpen-Source LLMs
Tech Stack
Tools & technologiesAzureCloudPythonTerraformVault
About the role
Key responsibilities & impact- Design, develop, and deploy AI agents capable of performing multi-step tasks and automating business workflows
- Build agents using Microsoft Foundry, Azure AI Agent Service, LangGraph, Semantic Kernel, or similar technologies
- Develop tool calling, function execution, retrieval-augmented generation, memory management, and workflow orchestration capabilities
- Integrate agents with internal applications, external APIs, databases, Microsoft Teams, SharePoint, Outlook, OneDrive, calendars, and other enterprise systems
- Implement multi-agent workflows, human-in-the-loop approvals, security guardrails, authentication, authorization, delegated permissions, application permissions, app registrations, and OBO flows
- Test, evaluate, and optimize agent accuracy, reliability, performance, latency, scalability, and cost
- Fine-tune and customize commercial and open-source LLMs, including Llama, Qwen, and Mistral
- Prepare training datasets, perform preprocessing, and develop model evaluation pipelines
- Apply LoRA and QLoRA and support model serving, quantization, and inference optimization
- Provision, configure, and manage Microsoft Azure infrastructure for AI applications
- Work with Azure AI Foundry, Azure OpenAI Service, Azure App Service, Azure Functions, Azure Container Apps, Azure AI Search, Azure Storage, databases, Azure Key Vault, Azure Monitor, Application Insights, and Microsoft Entra ID
- Build and maintain CI/CD pipelines using Azure DevOps
- Manage source control, deployments, and environment configurations using Git and Azure DevOps
- Support infrastructure as code using Terraform or Bicep
- Implement monitoring, logging, error handling, troubleshooting, and production maintenance
- Optimize cloud infrastructure for performance, reliability, security, and cost
- Collaborate with clients and deliver training or knowledge-transfer sessions when needed
Requirements
What you’ll need- 2–5 years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles
- Strong programming proficiency in Python, with experience developing backend services and APIs
- Practical experience developing LLM-powered applications, AI agents, or intelligent automation systems
- Experience with agent frameworks such as Microsoft Foundry Agent Service, LangGraph, Semantic Kernel, or equivalent tools
- Working knowledge of RAG, vector databases, embeddings, tool calling, and LLM orchestration
- Hands-on experience with Microsoft Azure, including deploying and managing cloud applications
- Experience using Azure DevOps, Git, and CI/CD pipelines
- Understanding of REST APIs, authentication, authorization, and enterprise system integrations
- Familiarity with Microsoft Entra ID, OAuth 2.0, and Microsoft Graph API
- Experience working with open-source LLMs and familiarity with model fine-tuning techniques
- Understanding of model evaluation, inference, and performance optimization
- Ability to discuss AI solutions with clients, translate technical concepts into business value, and deliver training or knowledge-transfer sessions when needed
Benefits
Comp & perks- Free lunch meal, fruits, snacks, and drinks (if you are in an onsite shift)
- Onsite gym with a free professional instructor
- Weekly fitness activity and an annual fitness challenge where you can win up to Php 70,000
- Weekly engagement activities with prizes that are up to Php 3,000
- Free upskilling academy to improve your performance and skillset
- State-of-the-art facilities from toilets to your workstation
- Amenities such as sleeping quarters, game area, chat room, shower room