Lead AI Engineer

VDart Inc; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

VDart Inc. is seeking a Lead AI Engineer to drive enterprise AI initiatives across .NET and Azure platforms.

This remote 6-month engagement requires hands-on expertise in Agentic AI, Generative AI, MCP, and AI-SDLC, with ability to design and orchestrate AI agents for requirements engineering, backlog generation, architecture, coding, testing, DevOps, and documentation. Candidates should have strong experience integrating with Azure DevOps, GitHub, Jira and other enterprise tools, plus a solid

Qualifications

• Experience with Agentic AI, Generative AI and Model Context Protocol (MCP).
• Hands-on design and orchestration of AI agents across requirements engineering, backlog generation, architecture, coding, testing and DevOps.
• Strong background in RAG, prompt engineering, and cloud-native .NET architectures.

Responsibilities

• Design and implement AI agents for end-to-end enterprise workflows.
• Integrate AI solutions with Azure DevOps, GitHub, Jira and other platforms.
• Contribute to governance, quality, and reusable AI assets for modernization programs.

Skills

Agentic AI

Generative AI

RAG

Prompt engineering

AI-SDLC

Education

Bachelor's or Master's in CS / EE / Math

Tools

Azure DevOps

GitHub

Jira

Job description

Job Title: Lead AI Engineer Location: Remote Duration: 6 Months

Job Description:

AI Engineer with expertise in Agentic AI, Generative AI, Model Context Protocol (MCP), AI Harnesses, and AI-first Software Development Lifecycle (AI-SDLC) for enterprise .NET and Azure solutions.
Hands-on experience designing and orchestrating AI agents for requirements engineering, backlog generation, architecture, code development, testing, DevOps, and documentation, while integrating with Azure DevOps, GitHub, Jira, and other enterprise engineering platforms.
Strong background in RAG, prompt engineering, and cloud-native .NET architectures, with a proven ability to accelerate delivery, improve engineering productivity, and establish governance, quality, and reusable AI engineering assets for large-scale enterprise modernization programs.

Job Responsibilities:

AI Engineer with expertise in Agentic AI, Generative AI, Model Context Protocol (MCP), AI Harnesses, and AI-first Software Development Lifecycle (AI-SDLC) for enterprise .NET and Azure solutions.
Hands-on experience designing and orchestrating AI agents for requirements engineering, backlog generation, architecture, code development, testing, DevOps, and documentation, while integrating with Azure DevOps, GitHub, Jira, and other enterprise engineering platforms.
Strong background in RAG, prompt engineering, and cloud-native .NET architectures, with a proven ability to accelerate delivery, improve engineering productivity, and establish governance, quality, and reusable AI engineering assets for large-scale enterprise modernization programs.

Education:

Bachelor's or Master's degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.