What You'll Do;

The AI/ML Engineer role will lead the architecture, development, and deployment of enterprise-grade Generative AI and machine learning solutions. This role will be responsible for designing intelligent assistants, custom orchestrators, and AI agents deeply integrated with Microsoft Copilot Studio, Azure OpenAI Service, Azure AI Search, and the broader Microsoft 365 platform. The ideal candidate will bridge state-of-the-art Large Language Models (LLMs), traditional machine learning practices, and production-ready enterprise applications that are secure, scalable, and aligned to business outcomes.

The AI/ML Engineer will work closely with business stakeholders, data teams, application teams, infrastructure teams, and security partners to identify high-value AI use cases, design robust solution architectures, and move prototypes into reliable production environments. This role requires strong hands-on engineering capability, practical experience with LLMOps/MLOps, and the ability to apply responsible AI principles across the full solution lifecycle.

• Lead the design of scalable AI, machine learning, and Generative AI solutions that address business problems and integrate effectively with enterprise applications and data platforms.
• Design, build, and deploy custom intelligent agents using Microsoft Copilot Studio to automate complex enterprise workflows and improve employee productivity.
• Develop custom Copilot extensions, plugins, and Microsoft Graph Connectors to securely ground LLMs in internal enterprise data and business processes.
• Architect and implement robust Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search and orchestration frameworks such as Microsoft Semantic Kernel, LangChain, or similar tools.
• Design, train, evaluate, fine-tune, and optimize machine learning and LLM-based solutions for accuracy, reliability, latency, throughput, and cost efficiency.
• Build and manage secure APIs, services, and Power Platform connectors to link Copilot experiences with legacy systems, third-party databases, and enterprise applications.
• Provision, configure, and optimize generative AI infrastructure within Azure OpenAI Service and related Azure services, including token consumption, throughput, latency, observability, and operational performance.
• Implement continuous integration, deployment, monitoring, testing, and versioning practices for AI models, prompts, embeddings, orchestration flows, and production services.
• Implement strict guardrails, prompt engineering standards, content filtering, responsible AI controls, and Azure AI Content Safety practices to ensure compliant and trustworthy AI outputs.
• Partner with cross-functional teams to translate business requirements into technical designs, document architecture and decisions, and communicate solution trade-offs to technical and non-technical stakeholders.

What You'll Bring;

• Proven experience implementing solutions with Azure OpenAI Service, Microsoft Copilot Studio, Azure AI Studio, Azure AI Search, and related Azure AI services.
• Advanced proficiency in Python or C# (.NET Core), with strong software engineering practices for building maintainable, secure, and production-ready services.
• Strong understanding of machine learning, deep learning, NLP, embeddings, semantic search, model evaluation, feature engineering, and model performance optimization.
• Deep knowledge of Microsoft Semantic Kernel, LangChain, LlamaIndex, or similar frameworks used to build orchestrated AI workflows and agentic applications.
• Experience with vector embeddings, semantic search optimization, and databases such as Azure Cosmos DB, Pinecone, or other vector-capable data platforms.
• Familiarity with Azure DevOps or GitHub Actions for managing continuous integration and deployment pipelines for AI models, prompts, APIs, and related services.
• Understanding of Microsoft 365 architecture, Microsoft Graph API, Azure Active Directory / Microsoft Entra ID, identity, permissions, and secure data access patterns.
• Ability to lead technical design discussions, mentor team members, document complex solutions, and collaborate effectively with business, security, infrastructure, and application stakeholders.
• Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related discipline.
• Senior-level experience designing, developing, and deploying AI/ML, Generative AI, or data-driven enterprise solutions in production environments.
• Hands-on experience moving AI prototypes into production, including security review, operational monitoring, performance tuning, and stakeholder adoption.
• Experience working in enterprise environments with cross-functional teams, secure data access requirements, governance standards, and integration with existing business systems.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Microsoft Certified: Power Platform Developer Associate (PL-400)

AI is used as part of our application review process to assist in screening and assessment. All applications are also reviewed by our recruitment team.

This posting is for an open new role in our organization.