Senior Azure AI Engineer (Hybrid)
Salary: ₱140,000 – ₱150,000 per month
Key Responsibilities:
Design, build, and deploy AI/ML models and end-to-end AI pipelines for production environments.
Integrate AI capabilities into applications and services using APIs and cloud-native architectures.
Develop and manage Prompt Flows, orchestration pipelines, and agent-based AI workflows.
Design and implement Retrieval-Augmented Generation (RAG) solutions, including embeddings, indexing, chunking, and context management.
Monitor, evaluate, and optimize AI model performance, accuracy, scalability, and cost.
Establish observability, logging, monitoring, and performance tracking for AI systems.
Apply secure-by-design principles, including identity management, access control, and data protection.
Ensure compliance with Responsible AI, model safety, governance, and security standards.
Collaborate with Data Engineers, Software Engineers, and Product Teams to ensure seamless data and system integration.
Translate business requirements into practical AI solutions by defining appropriate guardrails, KPIs, and success criteria.
Requirements:
Experience:
3–6+ years of experience 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 other major cloud platforms such as AWS or GCP.
Proven experience in prompt engineering, AI orchestration, or RAG-based solutions.
Experience working with cross-functional engineering, data, and product teams.
Technical Knowledge:
Strong knowledge of AI/LLM engineering, including prompt design, orchestration/Prompt Flow, agent-based systems, and RAG.
Proficiency in Python, REST/JSON APIs, microservices, and CI/CD practices.
Experience with the Azure AI ecosystem, including AI Foundry, model deployment, inference APIs, and cost optimization.
Knowledge of embeddings, chunking strategies, indexing, and Azure AI Search/hybrid retrieval.
Understanding of Azure networking, Microsoft Entra ID, observability, and secure-by-design architectures.
Knowledge of Responsible AI, including model safety, governance, explainability, and policy enforcement.
Familiarity with Copilot Studio and Power Platform extensibility is a plus.
Key Skills:
Ability to translate business problems into practical AI solutions.
Strong analytical and problem-solving skills, especially in ambiguous environments.
Ability to communicate complex AI concepts and probabilistic outputs to non-technical stakeholders.
Strong collaboration skills across Engineering, Data, and Product teams.
Ability to define AI guardrails, KPIs, and success criteria.
Why Join Us?
Work on cutting-edge AI/LLM and cloud technologies.
Opportunity to build and deploy AI solutions used in real-world production environments.
Collaborate with experienced Engineering, Data, and Product teams.
Career growth opportunities in the rapidly evolving AI space.
Apply now and be part of a team building the next generation of AI-powered solutions!
MGL