Infrastructure Engineer, AI & Data Security

Infrastructure Engineer, AI & Data Security at homevision. About the role Homevision is building MIRA, an artificial intelligence platform that transforms how the mortgage industry handles document processing and underwriting tasks through intelligent automation. This engineering position centers on constructing and maintaining the robust backend infrastructure necessary for deploying AI systems securely at scale. You will play a critical role in ensuring that document analysis capabilities expand reliably while maintaining the highest standards of data protection and system integrity. The ideal candidate brings both software engineering expertise and a deep appreciation for security considerations in modern cloud environments.

Key facts

• Location: Argentina (Rosario or Buenos Aires preferred)
• Engagement: Full-time position
• Compensation: $5,000 - $8,000 monthly, based on experience
• Team: Engineering department
• Residency requirement: Must be located in Argentina

What you'll do

• Design, build, and maintain secure infrastructure environments specifically tailored for artificial intelligence development, testing, and production deployment across the organization.
• Establish and enforce comprehensive data access controls throughout the entire platform, ensuring sensitive mortgage documentation remains protected at every stage of processing.
• Contribute to cross-functional application development by writing production-quality code in Go, Python, and TypeScript to support various platform features and integrations.
• Take ownership of complete project lifecycles, from initial architectural design and technical documentation through detailed planning phases and ongoing status communication with stakeholders.
• Champion system reliability and observability practices across all deployments, implementing monitoring solutions that provide visibility into system health and performance metrics.
• Collaborate with AI and machine learning teams to understand infrastructure requirements for large language model deployments and ensure environments support safe experimentation.
• Identify potential security vulnerabilities and data access risks proactively, implementing preventive measures before issues impact production systems or compromise sensitive information.
• Develop and maintain infrastructure automation scripts and configurations that enable consistent, repeatable deployments across development, staging, and production environments.
• Participate in incident response and troubleshooting activities, applying systematic approaches to diagnose and resolve infrastructure-related issues efficiently.
• Document architectural decisions, security protocols, and operational procedures to ensure knowledge sharing and maintain institutional understanding of critical systems.
• Evaluate and recommend new tools, technologies, and approaches that could enhance infrastructure security, reliability, or operational efficiency for the engineering organization.
• Work closely with product and business teams to understand upcoming feature requirements and ensure infrastructure capacity planning aligns with organizational growth objectives.

Requirements

• Demonstrated track record in backend software engineering with substantial hands-on experience building and maintaining production systems at scale.
• Security-first mindset in all development activities, including the ability to recognize data access risks, identify potential attack vectors, and implement appropriate protective measures.
• Genuine enthusiasm for the infrastructure challenges associated with deploying safe, reliable, and performant large language model and artificial intelligence systems in production environments.
• Practical experience or strong demonstrated interest in cloud infrastructure management using platforms such as Amazon Web Services, Google Cloud Platform, or infrastructure provisioning tools like Terraform.
• Proven ability to navigate complex, ambiguous technical projects independently, taking initiatives from initial concept and design phases through successful production deployment.
• Excellent written and verbal English communication skills, enabling effective collaboration with distributed team members and clear documentation of technical decisions.
• Strong problem-solving abilities with a systematic approach to debugging, performance optimization, and architectural decision-making in distributed systems contexts.
• Comfort working in fast-paced startup environments where priorities may shift and flexibility in approach is valued alongside technical excellence.

Nice to have

• Hands-on experience implementing Infrastructure-as-Code practices, particularly using Terraform for managing cloud resources in a version-controlled, reproducible manner.
• Working knowledge of observability and monitoring platforms such as Datadog, including experience configuring dashboards, alerts, and distributed tracing for complex applications.
• Background in Amazon Web Services architecture patterns, especially those involving network isolation strategies, sandboxed execution environments, and security primitives designed for high-throughput systems.
• Experience with container orchestration technologies and microservices architectures in production environments.
• Familiarity with compliance frameworks relevant to financial services or mortgage industry data handling requirements.
• Previous exposure to machine learning operations or platform engineering supporting data science teams.

Skills & tools

• Programming languages: Go, Python, TypeScript
• Cloud platforms: Amazon Web Services, Google Cloud Platform
• Infrastructure automation: Terraform, Infrastructure-as-Code methodologies
• Monitoring and observability: Datadog and similar platforms
• Security practices: Access control implementation, vulnerability assessment, network isolation
• Development practices: Documentation, project planning, cross-functional collaboration

Practical notes

• Candidates must currently reside in Argentina to be considered for this position; relocation from other countries is not supported for this role.
• All candidates who advance through the interview process must successfully complete comprehensive background verification, which includes criminal history checks, educational credential verification, employment history confirmation, and professional reference checks.
• Final compensation within the stated range will be determined based on relevant experience, technical skill level, and overall fit for the role requirements.
• The interview process will assess both technical capabilities and alignment with team culture and working style expectations.