We are seeking a hands-on AI Engineer to design, develop, and deploy AI agents and intelligent automation solutions for enterprise applications who can contribute across the full development lifecycle, from AI agent architecture and backend development to infrastructure deployment, authentication, testing, and production maintenance.
The role involves working with large language models (LLMs), including both commercial and open-source models, with opportunities to fine-tune, customize, evaluate, and optimize models for specific business use cases.
The ideal candidate must have strong software engineering skills, experience working with Microsoft Azure infrastructure, and the ability to develop AI agents that integrate securely with enterprise systems such as Microsoft Teams, SharePoint, Outlook, and other Microsoft 365 services.
Key Responsibilities:
AI Agent Development
Microsoft Azure & Enterprise Integrations
Open-Source LLMs & Model Fine-Tuning
Azure Infrastructure & DevOps
Requirements
What We’re Looking For
We are looking for a practical, technically capable engineer who enjoys building working AI systems and solving complex engineering problems who is not only knowledgeable in AI but also a hands-on practitioner who can confidently discuss AI solutions with clients, translate technical concepts into business value, and deliver training or knowledge-transfer sessions when needed.
The ideal candidate should be comfortable working across AI development, backend engineering, cloud infrastructure, and enterprise integrations. They should be able to take an AI agent from prototype to production, understand how to connect it securely to enterprise applications, and have the technical curiosity to experiment with open-source models and emerging AI frameworks.
This is a hands-on engineering role, not a prompt engineering or no-code automation position. We are particularly interested in candidates who can demonstrate working AI agents, real Azure deployments, enterprise integrations, or fine-tuned LLM projects they have personally developed.
Required Qualifications:
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
Preferred Qualifications:
Experience with AWS cloud services and architecture
Experience building and deploying AI agents within Microsoft Teams
Experience implementing OAuth On-Behalf-Of flows and delegated Microsoft Graph permissions
Experience with Microsoft 365 Agents SDK, Teams SDK, or Azure Bot Service
Hands-on experience fine-tuning open-source LLMs using LoRA, QLoRA, or Hugging Face PEFT
Experience deploying open-source models using vLLM, Ollama, Hugging Face, or similar serving frameworks
Familiarity with GPU infrastructure and model inference optimization
Experience with Docker, containerized applications, Terraform, or Bicep
Familiarity with Model Context Protocol (MCP), multi-agent systems, and agent orchestration
Experience integrating AI applications with SharePoint, Dynamics 365, SQL databases, or other enterprise systems
Familiarity with enterprise AI security, observability, and MLOps practices
Benefits
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
Summary
Build and deploy AI agents and intelligent automation solutions across the full development lifecycle, integrating with Microsoft 365, Azure infrastructure, and open-source LLMs. Requires 2–5 years of software or AI engineering experience, strong Python skills, hands-on Azure and agent framework experience, and knowledge of RAG, vector databases, and model fine-tuning.
Responsibilities
Design, develop, and deploy AI agents capable of multi-step tasks and automating business workflows; build agents using Microsoft Foundry, LangGraph, Semantic Kernel, or similar; develop agent capabilities including tool calling, RAG, memory management, and workflow orchestration; integrate agents with internal applications, external APIs, databases, and enterprise systems; implement multi-agent workflows, human-in-the-loop approvals, and security guardrails; test, evaluate, and optimize agent accuracy, reliability, and performance; build and deploy AI agents within Microsoft Teams and Microsoft 365; integrate with Microsoft Graph API; implement secure authentication and authorization using Microsoft Entra ID, OAuth 2.0, and SSO; develop backend APIs and services; work with commercial and open-source LLMs such as Llama, Qwen, and Mistral; fine-tune and customize LLMs using LoRA and QLoRA; prepare training datasets and develop model evaluation pipelines; experiment with inference optimization, quantization, and model serving; provision and manage cloud infrastructure in Microsoft Azure; build and maintain CI/CD pipelines using Azure DevOps; support infrastructure as code using Terraform or Bicep; implement monitoring, logging, and troubleshooting for production AI systems
Qualifications
2–5 years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles; strong Python proficiency with 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; 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
Experience requirements
2–5 years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles
Benefits
Free lunch meal, fruits, snacks and drinks (onsite shifts); onsite gym with free professional instructor; weekly fitness activity and annual fitness challenge with prizes up to Php 70,000; weekly engagement activities with prizes up to Php 3,000; free upskilling academy; state-of-the-art facilities; amenities including sleeping quarters, game area, chat room and shower room