Azure AI Engineer
Taguig City, Ncr-Fourth District
Design, build, and deploy AI models and end-to-end AI pipelines for production environments.Integrate AI capabilities into applications and services using APIs and cloud-native architectures.Collaborate with Data Engineers, Software Engineers, and Product Teams to ensure seamless data flow and system integration.Monitor, evaluate, and optimize model performance, accuracy, and scalability in real-world use.Develop and manage Prompt Flows, orchestration pipelines, and agent-based AI workflows.Implement Retrieval-Augmented Generation (RAG) solutions, including embedding, indexing, and context management.Ensure adherence to Responsible AI practices, including model safety, governance, and compliance standards.Establish observability, logging, and performance monitoring for AI systems.Apply secure-by-design principles, including identity management, access control, and data protection.Translate business requirements into AI solutions, defining guardrails, KPIs, and success criteria.
Qualifications
Bachelor’s degree in IT, Computer Science, or any related field.3–6+ years in AI/ML, software engineering, or cloud-based AI solution development.Hands-on experience building and deploying AI/LLM-powered applications in production. Experience with Azure or similar cloud platforms (AWS/GCP). Proven work on prompt engineering, orchestration, or RAG-based solutions. Experience collaborating in cross-functional product or engineering teams.Knowledge in AI/LLM engineering: prompt design, orchestration (Prompt Flow), agent-based systems, and RAG implementation. Knowledge in Software engineering: Python, APIs (REST/JSON), microservices, and CI/CD practices. Knowledge in Azure AI ecosystem: AI Foundry, model deployment, inference APIs, and cost optimization.Knowledge in Data and search: embeddings, chunking strategies, and Azure AI Search (hybrid retrieval). Knowledge in Cloud and security: Azure networking, identity (Entra ID), observability, and secure-by-design architectures. Knowledge in Responsible AI: model safety, governance, explainability, and policy enforcement.Knowledge in Low-code integration: Copilot Studio and Power Platform extensibility. Strong analytical thinking and problem-solving in ambiguous environments. Effective collaboration across engineering, data, and product teams. Ability to define guardrails, KPIs, and success criteria for AI solutions
Must Have
Bachelor’s degree in IT, Computer Science, or any related field.3–6+ years in AI/ML, software engineering, or cloud-based AI solution development.Hands-on experience building and deploying AI/LLM-powered applications in production.Experience with Azure or similar cloud platforms (AWS/GCP).Proven work on prompt engineering, orchestration, or RAG-based solutions.Experience collaborating in cross-functional product or engineering teams.Knowledge in AI/LLM engineering: prompt design, orchestration (Prompt Flow), agent-based systems, and RAG implementation.Knowledge in Software engineering: Python, APIs (REST/JSON), microservices, and CI/CD practices.Knowledge in Azure AI ecosystem: AI Foundry, model deployment, inference APIs, and cost optimization.Knowledge in Data and search: embeddings, chunking strategies, and Azure AI Search (hybrid retrieval).Knowledge in Cloud and security: Azure networking, identity (Entra ID), observability, and secure-by-design architectures.Knowledge in Responsible AI: model safety, governance, explainability, and policy enforcement.Knowledge in Low-code integration: Copilot Studio and Power Platform extensibility.Strong analytical thinking and problem-solving in ambiguous environments.Effective collaboration across engineering, data, and product teams.Ability to define guardrails, KPIs, and success criteria for AI solutions