AI Engineer

About the Role

We are looking for an AI Engineer to design, build, integrate, and optimize AI-powered services and intelligent systems that enhance employee experience and support real-world HR technology use cases. The role is hands-on and engineering-focused, with emphasis on secure, scalable, measurable, and maintainable AI application delivery

• Design and develop AI-powered services that enhance employee experience and support HR technology use cases.
• Integrate and optimize large language models and intelligent systems using Azure OpenAI and other cloud-native AI tools.
• Apply advanced AI architecture patterns such as Retrieval-Augmented Generation (RAG), Agentic RAG, MCP, Function Calling, and A2A to practical enterprise use cases.
• Engineer robust pipelines for prompt design, context handling, embeddings, chunking strategies, and real-time data integration.
• Evaluate, test, and optimize model output and application performance to improve relevance, robustness, fairness, and explainability.
• Implement guardrails, prompt testing, adversarial and bias testing, and other controls needed for responsible AI application delivery.
• Develop and deploy cloud-based AI applications at scale using Azure Cloud Services for AI, including Azure OpenAI and Azure AI Search.
• Ensure solutions are secure, reliable, observable, maintainable, and well documented.
• Understanding of alignment and feedback techniques, synthetic data generation, and continuous human-in-the-loop review loops.
• Experience designing evaluation approaches for relevance, groundedness, explainability, safety, robustness, and operational quality.
• Experience packaging AI features for production use with logging, monitoring, observability, and controlled rollout patterns.

• Excellent Python skills and hands-on experience
• Experience in AI application development, with focus on cloud-based AI model integration, deployment, and optimization.
• Experience with AI/ML and agentic application frameworks such as Lang Chain, Lang Graph, Pydantic
• Proficiency in advanced AI architecture patterns, including RAG, Agentic RAG, MCP, Function Calling, and A2A, especially in an Azure environment
• Good understanding of GPT token usage, latency analytics, and budget guardrails.
• Sound understanding of AI guardrails, prompt fuzzing, adversarial testing, and bias testing.
• Experience in prompt engineering, context engineering, vector databases, embedding and chunking strategies, and real-time data integration.
• Experience evaluating model output and optimizing AI application performance.
• Hands-on experience with Azure Cloud Services for AI, including Azure OpenAI and Azure AI Search.
• Strong commitment to quality, maintainability, documentation, and continuous learning.

Required AI services LLM integration RAG patterns prompt/context pipelines evaluation and Azure AI services