AI Engineer
Position Summary
Join our AI Enablement team and help accelerate enterprise-wide AI adoption. This role is designed for engineers passionate about applying AI to real-world business challenges. The successful candidate will work on rapid prototyping, automation, and integration of AI solutions that enhance productivity and innovation across diverse business areas.
Key Responsibilities
- Build and deploy AI-driven tools and workflows using platforms such as Copilot Studio, UiPath, and other automation frameworks.
- Connect AI agents with enterprise systems including SharePoint, Microsoft 365, external APIs, and knowledge bases.
- Identify repetitive tasks and develop intelligent automation solutions to improve efficiency.
- Partner with cross-functional teams to enable AI literacy, create best-practice ation, and support training initiatives.
- Collaborate with cybersecurity teams to ensure AI solutions meet security, ethical, compliance, and governance requirements.
- Ensure secure agent interactions using encryption, authentication, and authorization mechanisms.
- Integrate solutions with identity platforms including OAuth2, OIDC, SAML, Entra ID, and AD FS.
- Continuously improve solutions through feedback, iteration, and scalable innovation.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, or a related field.
- Minimum 5 years of software development experience, including at least 2 years focused on AI/ML engineering.
- Strong understanding of AI concepts, machine learning pipelines, and automation tools.
- Hands-on experience with Copilot Studio, UiPath, and SharePoint.
- Experience with cloud AI platforms including Azure AI Foundry, AWS Bedrock, and/or Google Vertex AI.
- Knowledge of retrieval-augmented generation (RAG), semantic chunking, memory persistence, and scalable context management.
- Experience implementing multi-agent workflows and agent orchestration frameworks.
- Ability to design and manage context-aware systems leveraging Model Context Protocol (MCP), prompt engineering, memory management, and context optimization.
- Familiarity with A2A (Agent-to-Agent) frameworks and integrations.
- Strong development skills in .NET, C#, Python, Java, APIs, SQL, PowerShell, and Unix shell scripting.
- Experience with cloud platforms, API integrations, and data quality validation.
- Strong communication, collaboration, and problem-solving skills.
Preferred Qualifications
- Exposure to Generative AI, prompt engineering, and agent-based systems.
- Interest in AI governance, security, and ethical frameworks.
- Ability to deliver quick wins while maintaining enterprise standards.