.Net Architect Contractor: 10+ years (Expert)

• Experience building, delivering, or supporting AI-enabled solutions using Large Language Models (LLMs), Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), vector databases, AI orchestration frameworks, or related AI technologies in enterprise environments.
• Understanding of Responsible AI principles, including AI governance, security, privacy, transparency, human oversight, and model evaluation best practices.
• Demonstrated ability to effectively leverage AI tools and assistants to improve individual productivity, accelerate delivery, enhance decision-making, automate routine tasks, and improve quality across day-to-day work activities.
• Strong AI literacy, including the ability to evaluate AI-generated outputs, apply critical thinking and human judgment, and identify appropriate use cases for AI-driven solutions.
• Preferred: Hands-on experience with Python and/or .NET technologies for developing, integrating, and operationalizing AI-enabled applications and services.
• Continuous learner with a passion for staying current on emerging AI technologies, practices, and industry trends.

Preferred Skills (Recommended for All Engineering-Focused Applied AI Roles)
• Experience with Python, .NET, cloud-native application development, APIs, microservices, and modern software engineering practices.
• Experience with Azure OpenAI, Azure AI Foundry, Microsoft Copilot technologies, AI orchestration frameworks, vector databases, and enterprise AI platforms.
• Experience developing, integrating, deploying, or operating AI-enabled applications in Azure cloud environments.
• 6+ years of full-stack software engineering experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit and integration testing frameworks.
• 3+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration.
• 3+ years of experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering (FinOps accountability)
• Prior experience in establishing engineering standards, including actively leading, mentoring, and guiding team members in the adoption and continuous improvement of these standards.
• Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.