Senior Software Engineer – AI Modernization

This is a fully remote position, open to applicants in Mexico, +1 more country.

📋 Description

• Design, develop, maintain, and troubleshoot enterprise-level applications.

• Modernize legacy systems and transition outdated technologies into contemporary application architectures.

• Evaluate applications to decide if functionality should be refactored, rebuilt, replaced, or migrated.

• Segment modernization initiatives into manageable, testable phases while ensuring business functionality and minimizing technical debt.

• Create and develop APIs, services, integrations, and reusable application components.

• Build AI-enhanced applications, workflows, assistants, agents, and automation solutions.

• Integrate AI/LLM capabilities into business applications, assessing their accuracy, security, reliability, maintainability, and operational value.

• Collaborate with database/data resources on data models, integrations, and performance optimization.

• Investigate application defects and production issues to identify root causes and resolutions.

• Review code to identify architecture, maintainability, security, and performance risks.

• Engage in technical design and architectural decision-making processes.

• Develop both automated and manual testing strategies for development and modernization projects.

• Support DEV, TEST/UAT, and PROD release cycles.

• Define rollback or recovery strategies for major production changes.

• Maintain technical documentation for applications, integrations, architecture, APIs, and deployment procedures.

• Monitor status, estimates, blockers, risks, and target deadlines.

• Collaborate with BA, PM, DB/Data, Infrastructure, Applications, Security, and Support teams.

• Create AI-enabled internal tools and business applications.

• Work with LLM APIs and AI platforms.

• Develop AI agents and automate workflows.

• Implement structured prompting, tool/function calling, APIs, and application integration.

• Link AI solutions to approved enterprise data sources.

• Design validation and human review processes for AI outputs impacting business decisions.

• Assess the quality and reliability of AI outputs.

• Implement logging, monitoring, access control, and failure management.

• Transition AI initiatives from prototype phases to supportable production solutions.

⛳️ Requirements

• Strong enterprise software development background, particularly in JavaScript, TypeScript, Go, and Python.

• Experience with modern application architecture.

• Knowledge of legacy application modernization.

• Proficiency in API design and integration.

• Familiarity with REST APIs and web services.

• SQL and relational database expertise.

• Object-oriented application development skills.

• Experience with Git/source control.

• Knowledge of CI/CD and application deployment practices.

• Application troubleshooting and root cause analysis experience.

• Skills in testing and release management.

• Secure application development knowledge.

• Experience integrating third-party systems and services.

• Experience with various AI technologies, including LLM APIs, AI application development, AI agents, prompt engineering, tool/function calling, RAG, vector search/embeddings, AI workflow automation, enterprise AI integration, AI evaluation and validation, and Microsoft/Azure AI technologies.

• Preferred: Familiarity with Microsoft technology environment.

• Preferred: Experience with Azure/AWS.

• Preferred: Background in enterprise application modernization.

• Preferred: Knowledge of healthcare or skilled nursing environments.

• Preferred: Experience with internal business applications.

• Preferred: Large legacy application conversion experience.

• Preferred: Application and database integrations, such as DynamoDB, MongoDB, and Aurora DB.

• Preferred: Experience with automation platforms like Jenkins.

• Preferred: Familiarity with the Microsoft Power Platform/Copilot ecosystem.

🏝️ Benefits

• Equal Opportunity Employer.

• An inclusive workplace dedicated to diversity.

• Nearshore model that promotes speed, efficiency, and cultural alignment.