Develop AI and data strategy aligned with business goals and governance standards.
Design scalable data pipelines, architectures, and frameworks to support LLM training and deployment.
Leverage Microsoft CoPilot Studio and generative AI tools to build and integrate custom AI copilots and conversational agents.
Develop, fine-tune, and evaluate LLM-based chatbots and domain-specific AI assistants for enterprise functions.
Collaborate with teams (data engineers, product managers, and partners) to identify use cases and deliver AI-driven value.
Establish data management, lifecycle governance, and model security best practices.

Requirements

5 Years of experience across data science, AI, or data architecture roles.
Certifications in AI or Cloud Architecture (Azure AI Engineer, Data Engineer)
Experience with Large Language Models (LLM) such as OpenAI, Azure OpenAI, Hugging Face, Anthropic.
Expertise with Microsoft CoPilot Studio, Power Platform, or similar generative AI ecosystems.
Advanced programming skills in Python, SQL, and knowledge of data engineering frameworks.
Proficiency in cloud AI platforms (Azure AI, AWS Sagemaker, or GCP Vertex AI).
Understanding prompt optimization, retrieval-augmented generation, and model deployment pipelines.
Experience designing production-grade chatbots and AI agents.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

data strategydata pipelinesarchitecturesframeworksLLM trainingLLM-based chatbotsPythonSQLdata engineeringprompt optimization

collaborationcommunication

Azure AI EngineerData Engineer