Lead/Expert .NET Engineer (AI) - GP, Remote: Colombia - Costa Rica, Fulltime.

- This position is open to candidates located in Colombia or Costa Rica only -
Expert .NET Engineer (AI)

The Expert .NET Engineer (AI) plays a critical role in shaping and evolving application architecture to deliver scalable, high-performing, intelligent, and business-aligned solutions. This role operates at a deep technical level, driving modernization efforts, improving system performance, introducing AI-enabled capabilities, and ensuring applications integrate seamlessly within the enterprise ecosystem.

The ideal candidate combines strong hands-on development expertise with architectural thinking, modernization experience, and practical exposure to AI-assisted and agentic software development. This person should be comfortable designing and building traditional enterprise applications while also exploring how AI agents, automated workflows, and orchestration patterns can be incorporated into modern application architectures.

The ideal candidate does not need to be a Machine Learning Engineer or Data Scientist. However, they should have hands-on experience building AI agents, agentic workflows, or AI-powered automation using Claude Code or comparable AI development tools and frameworks. Candidates who can clearly explain concrete examples of agents or workflows they have personally designed, built, integrated, or orchestrated will meet this expectation.
Key Responsibilities

Technical Leadership and Delivery

- Develop high-quality code aligned with sprint commitments and enterprise standards.

- Lead modernization initiatives, including migrating legacy .NET applications such as .NET 3.5 systems to .NET Core.

- Break apart monolithic applications into scalable microservices architectures.

- Design robust, scalable, and highly available systems that support evolving business needs.

- Ensure applications follow security-first principles to protect customer data.

- Collaborate with other architects to align designs with enterprise architecture standards.

- Produce architectural diagrams and system representations to clearly communicate solution designs.

- Present technical roadmaps and architectural decisions to engineering teams and stakeholders.

AI Agents and Agentic Development

- Design, build, and integrate AI agents and AI-powered workflows into enterprise applications and engineering processes.

- Develop multi-step agentic workflows where AI models can reason across tasks, invoke tools, interact with APIs, process contextual information, and coordinate actions.

- Orchestrate AI agents and workflows using Claude Code or comparable AI development tools, agent frameworks, LLM platforms, or orchestration technologies.

- Integrate AI capabilities with existing APIs, services, databases, development workflows, and enterprise systems.

- Build practical AI-driven automations that improve developer productivity, operational efficiency, application capabilities, or business processes.

- Understand how to structure prompts, context, tools, instructions, and workflow logic to produce reliable agent behavior.

- Evaluate when an AI agent is appropriate compared with traditional deterministic application logic.
Consider security, permissions, data privacy, observability, reliability, and error handling when introducing AI agents into enterprise environments.

- Prototype AI-enabled solutions and translate successful experiments into maintainable production-ready implementations.

- Clearly explain previous AI implementations, including the problem being solved, agent or workflow architecture, tools used, integrations, orchestration approach, and resulting outcome.

Database and Performance Optimization

- Write advanced SQL queries and optimize performance using indexing strategies and query plan analysis.

- Refactor legacy systems by moving business logic out of stored procedures when appropriate.

- Create and maintain DDL scripts and stored procedures as needed.

- Ensure data integrity, scalability, and perform