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 performance across relational and non-relational databases.

Cloud and DevOps

• Design and deploy solutions in Microsoft Azure, leveraging cloud-native services.
• Work with Azure DevOps pipelines and tools such as Octopus for CI/CD automation.
• Apply DevOps best practices to improve deployment reliability and speed.
• Experience with AWS is valuable, but strong Azure expertise is required.

Full-Stack Development

• Develop backend services using C#, .NET Core, .NET Framework, Web APIs, and service-based architectures.
• Build and support modern front-end applications using frameworks such as Angular, React, and Vue.js.
• Demonstrate proficiency in JavaScript, TypeScript, and Node.js environments.

Required Qualifications

• High school diploma or equivalent required.
• Bachelor’s degree in Computer Science or related field preferred.
• 8 to 10 years of software development experience with technical leadership responsibilities.
• Strong full-stack C# development experience within the Microsoft technology stack.
• Proven experience migrating legacy .NET systems to modern architectures.
• Advanced SQL skills including query optimization, indexing strategies, and performance tuning.
• Experience with CI/CD tools such as Azure DevOps and Octopus.
• Experience working with legacy technologies such as VB.NET is valuable.
• Hands-on experience with Angular and React, with exposure to Vue.js preferred.
• Strong Azure cloud development experience required.
• Hands-on experience building AI agents, agentic workflows, or AI-powered automation.
• Experience orchestrating AI workflows involving multiple steps, tools, APIs, services, or agents.
• Practical experience using Claude Code or comparable AI coding, agent development, or LLM tooling.
• Ability to provide clear examples of AI agents or workflows personally designed, developed, integrated, or orchestrated.
• Understanding of how LLM-powered capabilities can be safely and effectively integrated into enterprise applications.

Preferred Skills

• Experience with Anthropic Claude, Claude Code, Azure AI, OpenAI APIs, or other enterprise LLM platforms.
• Experience with AI orchestration frameworks such as Semantic Kernel, LangChain, LangGraph, AutoGen, or similar technologies.
• Knowledge of VB6, MS SQL Server XML, XSL, ETL, Web Services, SOA, ASP.NET MVC, PowerShell, NoSQL and object databases.
• Azure cloud certifications preferred.
• AWS or Google Cloud certifications are a plus.
• Experience in financial services or other highly regulated industries is desirable.
• Behavioral and Leadership Expectations
• Strong communication skills with the ability to clearly explain complex architectural concepts to both technical and non-technical stakeholders.
• Ability to structure and articulate reasoning in a logical, easy-to-follow manner.
• Collaborative and approachable team player who contributes positively to team culture.
• Proactive problem solver with curiosity and determination in tackling complex challenges.
• Customer-focused mindset with strong attention to quality and testability.
• Ability to influence stakeholders and drive alignment in complex technical environments.