W
Agentic Systems Engineer (TypeScript, .NET, MCP) - Remote
Contract type
Freelance
Work mode
Remote · Eastern Europe
Experience
Mid-level · 4+ years
Job description
Architect and modernize legacy enterprise software codebases into modular, agent-operable systems for a client that acquires and transforms software companies into AI-native businesses. The role combines software architecture, AI-agent orchestration and engineering governance.
At a glance
- Employment
- Contract · Independent contractor
- Work mode
- Remote · Eastern Europe
What you'll do
- Decompose legacy monoliths into agent-readable, modular systems with strict boundaries and single responsibility
- Lead incremental modernization using the Strangler Pattern, wrapping legacy logic in modern, contract-driven interfaces
- Enforce SOLID principles, Dependency Injection, and Hexagonal Architecture to ensure deterministic AI execution and low regression risk
- Architect and maintain the agent context layer: standardized Skills, Rules, and Commands for AI-driven engineering workflows
- Build and operate Model Context Protocol (MCP) servers exposing legacy APIs, services, and databases as typed, secure, AI-consumable tools
- Own contract-first API design as the primary interface between human intent and autonomous agent execution
- Act as architectural gatekeeper for AI-generated pull requests, ensuring scalability, security, and long-term maintainability
- Mandate test-driven development (TDD) and characterization testing to preserve legacy behavior during refactoring
- Monitor and optimize agentic reasoning loops to balance cost, speed, and architectural integrity
What we're looking for
- 4+ years in software architecture, platform engineering, or technical leadership
- Proven experience modernizing large, undocumented legacy systems
- Deep hands-on expertise with TypeScript, .NET, and Node.js
- Strong background in API design, distributed systems, and modular architectures
- Practical experience with agentic development, MCP, LLM tooling, or AI-assisted engineering
- Bias toward clean code, deterministic systems, and production-grade AI
Nice to have
- Experience with remote-first or globally distributed teams
- Background in SaaS transformations, scale-ups, or PE-backed environments
- Comfort operating in high-ambiguity, high-ownership settings
Apply
About WLG
Acquires enterprise software companies and turns them into AI-native, profitable, scalable businesses. Remote-first, AI-forward team spread across the globe.
Key facts
- Remote-first, AI-forward team spread across the globe
- Offers high ownership, flexibility and impact
- Work across multiple products and technologies
- Growth pathways across engineering, product and leadership