Senior Azure AI Engineer (Hybrid)

Lewis Personnel Management; Taguig; Hybrid; PHP 1,200,000 - 1,800,000; Full time

Job summary

Lewis Personnel Management is seeking an experienced AI/ML Engineer to design, build, and deploy models and end-to-end AI pipelines for production environments.

You will integrate AI capabilities into applications via APIs and cloud-native architectures, develop prompt flows, RAG solutions, and ensure secure-by-design practices while upholding Responsible AI standards. Collaboration with Data, Software, and Product teams is essential in a fast-paced Manila-based setting.

Qualifications

• 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.

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.

Skills

AI/LLM engineering

Prompt design

RAG-based solutions

Python

CI/CD

Azure

Embeddings

Observability

Security

Cloud architectures

Tools

Azure AI Foundry

Azure AI Search

Copilot Studio

Power Platform

Job description

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

• 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.

MGL