Platform Tech Lead (AI)

TL;DR

Platform Tech Lead (C#/.NET, AI): Building and evolving a cloud-native platform, scalable backend services, and developer infrastructure that support hirify.global’s R&D teams with an accent on microservices architecture, reliability, security, and developer experience. Focus on designing high-performance distributed systems, driving cross-team technical decisions, and using AI-assisted development workflows while validating code quality and performance.

Location: Tel Aviv R&D

Company

hirify.global provides an AI-powered IT management platform combining remote monitoring and management, helpdesk, ticketing, automation, and reporting for IT professionals.

What you will do

• Design, build, and maintain scalable backend services with C# and .NET Core.
• Lead the architecture and evolution of a cloud-native platform based on microservices.
• Build infrastructure and developer platforms that improve engineering productivity.
• Work with Kubernetes, Docker, and major cloud platforms including Azure, AWS, and GCP.
• Drive decisions around scalability, reliability, security, performance, testing, and observability.
• Mentor engineers and influence technical direction across multiple teams.

Requirements

• 4+ years of experience building cloud-native systems with Azure, AWS, or GCP.
• Expert-level proficiency in C# and .NET Core, with hands-on experience building scalable RESTful microservices.
• Strong experience with Kubernetes, Docker, Platform Engineering or Infrastructure Engineering.
• Knowledge of relational and NoSQL databases, including MSSQL and MongoDB.
• Daily hands-on experience with AI coding tools such as Cursor, Claude Code, or GitHub Copilot.
• Ability to work with spec-driven development, validate AI-assisted implementations, and communicate technical decisions across teams.

Nice to have

• Experience configuring AI development tools, MCP servers, custom instructions, or reusable prompt libraries.
• Experience optimizing large-scale distributed systems.
• Knowledge of performance optimization, memory management, and .NET garbage collection.

Culture & Benefits

• Ownership, transparency, autonomy, and continuous learning.
• Opportunity to influence platform capabilities across the R&D organization.
• Hands-on work on complex cloud, distributed systems, and AI-assisted engineering challenges.