Lead AI .Net Developer

Original job posting

Build and deploy production-grade C#/.NET agentic AI workflows and automation to improve software development lifecycle processes, including requirements translation, code generation, and test creation. Integrate tools with GitHub and Microsoft developer ecosystems, optimize token costs, enforce security and quality guardrails, and coach engineering teams while relaying feedback to the Lead AI Engineer.

Job details

Description: Role Summary We are looking for a highly hands-on, execution-focused Lead AI Developer to serve as the ground-level technical partner to our Lead AI Engineer. While the Lead AI Engineer establishes the architectural vision and transformation roadmap, you will be the core builder in the trenches—writing production-grade C#/.NET code, engineering stateful agentic workflows, and implementing automated pipelines. Your primary mission is to revolutionize our Software Development Life Cycle (SDLC) and supercharge developer productivity by building, tuning, and deploying agentic AI tools that seamlessly integrate into clients' modern Microsoft and GitHub engineering ecosystem across multiple teams. Responsibilities Hands-on Agentic SDLC Implementation: Build, test, and deploy stateful multi-agent workflows, tool/function-calling mechanisms, and structured LLM output parsers in C#/.NET to automate software development life cycle (SDLC) stages (requirements translation, automated code generation, and test suite creation). Enterprise Spec-Driven Development Execution: Translate specs, JSON schemas, and structured technical specifications into machine-readable formats that drive autonomous multi-agent code and test generation across repositories. Developer Productivity & Tooling Integration: Develop custom extensions, plugins, and automation scripts integrated into GitHub Copilot, GitHub Actions, and Microsoft developer toolchains to streamline developer workflows and reduce cognitive load. Direct Engineering Team Uplift & Pair Programming: Work directly in the trenches with engineering teams through pair programming, live debugging, and hands-on guidance to demonstrate how to effectively adopt agentic AI tools in daily development. Token Optimization & FinOps Execution: Implement and fine-tune technical token optimization strategies—including context-window management, prompt caching, and hybrid routing between Small Language Models (SLMs) and frontier models—to minimize operational token costs. Guardrail Enforcement & Code Quality: Implement the engineering guardrails, security validations, and code-quality parsers defined by the Lead AI Engineer to ensure safe, compliant, and production-ready AI-generated code. Ground-Level Feedback Loop: Gather tactical, daily feedback from developers regarding workflow friction points and report back to the Lead AI Engineer to continuously refine prompt sets, agent loops, and developer experience (DevEx). Requirements Preferred Github Copilot (advanced) with GH-600/300 certification Hands-on C# & .NET Engineering Expertise: Strong, current coding proficiency in modern C# and .NET Core, with a deep understanding of Architecture, cloud-native patterns, and building robust backend tooling. Practical Agentic AI & LLM Experience: Proven hands-on experience building production-grade LLM applications, stateful agent execution loops, structured outputs (JSON mode/function calling) using GitHub Co Pilot SDLC Automation & GitHub Mastery: Practical experience automating software engineering pipelines, custom extensions, and CI/CD workflows using GitHub Actions, GitHub Copilot, and modern developer tooling. Familiarity with Spec-Driven Development: Solid understanding of how to use structured schemas (JSON Schema) to guide automated code generation and multi-agent workflows. Developer Productivity & DevEx Empathy: An acute understanding of developer friction points in the SDLC, with a passion for building tooling that enhances developer flow, joy, and velocity. Collaborative & Pragmatic Execution Style: Action-oriented, deeply hands-on, and eager to work side-by-side with engineering teams to coach them through real-world agentic transformations.

What you’ll do

Build and deploy production-grade C#/.NET agentic AI workflows and automation to improve software development lifecycle processes, including requirements translation, code generation, and test creation. Integrate tools with GitHub and Microsoft developer ecosystems, optimize token costs, enforce security and quality guardrails, and coach engineering teams while relaying feedback to the Lead AI Engineer.

Requirements

Requires strong, current C#/.NET engineering skills, practical experience building production LLM applications and stateful agent workflows, and familiarity with structured outputs and JSON Schema. Candidates should also have experience with GitHub Copilot, GitHub Actions, CI/CD automation, and developer productivity tooling; advanced GitHub Copilot skills and GH-600/300 certification are preferred.

Listed skills

• CI/CD · Preferred
• .NET · Preferred
• C++ · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• C#
• .NET
• Agentic AI
• Large Language Models
• Multi-Agent Workflows
• GitHub Copilot
• GitHub Actions
• CI/CD
• JSON Schema
• Function Calling
• Prompt Optimization
• Token Optimization
• Cloud-Native Architecture
• Pair Programming
• Developer Experience
• Code Quality

Job areas

• Software
• Technology
• Engineering
• Data & Analytics