AI Engineer - Agentic AI & Cloud Infrastructure
New
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iSupport WorldwideAI software
Workable workplace: remote; Workable locations: Metro Manila, PhilippinesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 2–5 years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles
- Required Skills
- PythonMicrosoft AzureAzure DevOps
Requirements
- Have 2–5 years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles.
- Demonstrate strong Python programming skills and experience developing backend services and APIs.
- Have practical experience developing LLM-powered applications, AI agents, or intelligent automation systems.
- Have experience with agent frameworks such as Microsoft Foundry Agent Service, LangGraph, or Semantic Kernel, or equivalent tools.
- Understand RAG, vector databases, embeddings, tool calling, and LLM orchestration.
- Have hands-on experience deploying and managing cloud applications in Microsoft Azure.
- Have experience using Azure DevOps, Git, and CI/CD pipelines.
- Understand REST APIs, authentication, authorization, and enterprise system integrations.
- Be familiar with Microsoft Entra ID, OAuth 2.0, and Microsoft Graph API.
- Have experience with open-source LLMs and familiarity with model fine-tuning, evaluation, inference, and performance optimization.
- Preferred: Experience with AWS, Microsoft Teams agents, Microsoft 365 Agents SDK, Teams SDK, or Azure Bot Service.
- Preferred: Experience with LoRA or QLoRA, Hugging Face PEFT, vLLM, Ollama, GPU infrastructure, Docker, Terraform, or Bicep.
Responsibilities
- Design, develop, and deploy AI agents that perform multi-step tasks and automate business workflows.
- Build agent capabilities for tool calling, function execution, RAG, memory management, and workflow orchestration.
- Integrate agents with internal applications, external APIs, databases, and enterprise systems.
- Build agents for Microsoft Teams and other Microsoft 365 applications, integrating with Microsoft Graph API.
- Implement authentication and authorization using Microsoft Entra ID, OAuth 2.0, SSO, and delegated or application permissions.
- Fine-tune and customize commercial and open-source LLMs, and prepare datasets and model evaluation pipelines.
- Evaluate models and optimize inference, quantization, serving, accuracy, reliability, and performance.
- Provision and manage Azure infrastructure and maintain CI/CD pipelines using Azure DevOps.
- Monitor, troubleshoot, and optimize production AI systems for performance, reliability, security, and cost.
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