Senior Full Stack Engineer – .Net/C#

Job Description

What You’ll Do :

– Rapid Feature Prototyping : Use AI agents to move from a concept or “vibe” to a working MVP in hours, not weeks.

– Context Management : Expertly manage IDE context (using .cursorrules, MCP servers, or project indexing) to ensure AI outputs adhere to Kibo’s specific architectural standards.

– Full-Stack Orchestration : Lead the development of complex .NET microservices and React frontends, utilizing AI to handle 80% of the manual coding while you focus on the critical 20% of logic and integration.

– AI-First Testing : Utilize AI to generate comprehensive test suites (nUnit, Jest, Playwright) that ensure high coverage and prevent regressions in an accelerated delivery environment.

– Code Quality & Review : Act as the final gatekeeper, ensuring that AI-generated code is not just “functional” but follows SOLID principles, security best practices, and performance standards.

– Database & Messaging : Architect data solutions in PostgreSQL and MongoDB, using AI to optimize queries and implement RabbitMQ event patterns.

Requirements :

What You’ll Need :

– 7+ years of software engineering experience, with the last 1-2 years focused heavily on AI-augmented workflows.

– AI Mastery (Required) : Deep expertise in prompt engineering, context engineering, and the use of AI Agents (e.g., Cursor’s Agent Mode, GitHub Copilot Extensions, or specialized CLI agents).

– Latest .NET Expertise : Advanced knowledge of .NET 8/9+ and C#. You must know how to prompt for the latest syntax and framework features.

– React & Modern Web : Mastery of React, TypeScript, and modern state management (Zustand, TanStack Query).

– The “Kibo Stack” : Proven experience with PostgreSQL, MongoDB, Redis, and RabbitMQ.

– Node.js Proficiency : Ability to navigate and build in Node.js environments when needed.

– Product Mindset : You don’t just “take tickets”; you use AI to explore solutions and proactively propose feature improvements.

Preferred Skills :

– Experience with Model Context Protocol (MCP) to connect AI tools to local and remote data sources.

– Familiarity with Agentic Frameworks (LangGraph, CrewAI) or custom AI-orchestration scripts.

– Experience in Performance Tuning for AI-generated code (e.g., identifying inefficient loops or redundant API calls).

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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