[Hiring] Agentic Systems Engineer @WLG

Role Description

Want to design the architecture that lets AI agents safely refactor, test and ship production code? Then let's talk.

The job: transform a 10+ year legacy codebase into a high-velocity, agent-operable architecture, at the intersection of software architecture, AI-agent orchestration and engineering governance.

Contract Type: Contract, full-time

Location: Fully remote from Eastern Europe, working US morning hours (Scrum).

What you'll do

• Agent-operable system architecture
  • 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
• Agentic framework & MCP leadership
  • 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
• Engineering governance & AI quality control
  • 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

Qualifications

• 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