Staff Engineer, IT, AI Enablement

AI Solution Development: Build and deploy AI-driven tools and workflows using platforms like Copilot Studio, UiPath, and other automation frameworks. Integration & Enablement: Connect AI agents with enterprise systems (e.g., SharePoint, M365), external APIs, knowledge bases, and ensure seamless interoperability. Process Automation: Identify repetitive tasks and design intelligent automation solutions to improve efficiency. Collaboration & Training: Partner with cross-functional teams to enable AI literacy, create best-practice documentation, and support internal training sessions. Governance & Compliance: Collaborate with cybersecurity teams to enforce data protection, threat modeling and ensure all AI solutions adhere to security, ethical, and compliance standards. Security & Identity Integration Ensure secure agent interactions using encryption, authentication, and authorization mechanisms. Integrate agents with identity platforms (e.g., OAuth2, OIDC, SAML, Entra ID, AD FS, etc.) for secure access control. Continuous Improvement: Collect feedback, iterate solutions, and contribute to a culture of innovation and scalability. Bachelor's or master's degree in computer science, AI, Machine Learning, Data Science or related field. Professionals with a minimum of 8 years of experience in software development, including at least 2 years specializing in AI/ML engineering. Strong understanding of AI concepts, machine learning pipelines, and automation tools. Hands-on experience or coursework in Copilot Studio, UiPath, and SharePoint. Knowledge with cloud AI platforms: Azure AI Foundry, AWS Bedrock, and/or Google Vertex AI. Knowledge with scalable context management solutions including retrieval-augmented generation (RAG), semantic chunking, and memory persistence for long-horizon tasks Implement multi-agent workflows for complex tasks such as decision-making, negotiation, and collaborative problem-solving. Ability to design, implement, and manage context-aware systems that leverage Model Context Protocol (MCP) to maintain continuity across user interactions, including prompt engineering, memory management, and context window optimization for large language models. Familiarity with cloud platforms, API integrations, and data quality validation. Familiarity with agent orchestration frameworks and multi-agent systems using A2A (Agent to Agent). Knowledge of common development languages .Net, C#, Python, Java, API development, SQL, PowerShell, Unix shell scripting Excellent problem-solving skills and ability to work in fast-paced, agile environments. Strong communication skills for cross-team collaboration. Exposure to generative AI, prompt engineering, or agent-based systems. Interest in AI governance, security, and ethical frameworks. Ability to adapt quickly and deliver “quick wins” while maintaining enterprise standards.