Sr. Software Engineer - Enterprise Platform - LATAM

Required Skills & Experience

5+ years of professional software engineering experience, including ownership of backend services in production. Deep mastery of computer science, programming, and software engineering fundamentals. Demonstrated mastery of at least one backend programming language. Strong hands-on backend engineering experience with the ability to own a production service or system end-to-end. Experience designing and building high-performance, scalable APIs and distributed backend services. Strong understanding of scalability, concurrency, fault tolerance, performance, reliability, and system architecture. Ability to clearly explain technical tradeoffs and decisions around architecture, performance, scalability, and cost. Ability to quantify production experience through metrics such as throughput, latency, traffic, users, events, or system scale. Strong practical engineering judgment with a demonstrated ability to move quickly, execute, and create measurable impact. Ability to operate at an architectural level while remaining deeply hands-on with code. Demonstrated ability to work independently, take ownership, and execute without significant PM/PO direction. Strong technical leadership through execution, architecture decisions, code reviews, and mentoring. Experience with REST and/or gRPC services. Experience working with cloud-native applications and Kubernetes environments. Experience using AI-assisted coding tools as part of day-to-day software development. Ability to explain how AI-generated code is reviewed, tested, validated, and safely incorporated into production systems. Comfortable working remotely with a distributed LATAM/PST-based engineering team.

Nice to Have Skills & Experience

Strong hands-on experience with Go, particularly production backend services. Experience with Node.js/TypeScript, Java, Perl, or additional backend languages. Experience building or shipping LLM-powered features into production. Experience designing or implementing multi-agent / agentic LLM workflows. Experience building or integrating MCP servers or other AI-agent tooling. Hands-on experience with AI development tools such as Claude Code, Codex, or Cursor. Experience designing AI evals, guardrails, regression testing, prompt-injection protection, or human-in-the-loop workflows. Experience with Kafka or other event-driven/streaming architectures. Experience with AWS and/or GCP. Experience running production services on Kubernetes, EKS, or GKE. Experience with Terraform, Helm, and enterprise CI/CD pipelines. Experience with observability platforms such as Prometheus, Grafana, or OpenTelemetry. Experience with Redis, MongoDB, or ETL/data pipeline environments. Experience modernizing or refactoring legacy services into modern backend architectures. Experience serving as a technical leader while remaining an individual contributor. Strong bonus for candidates who have shipped LLM-powered functionality, agentic workflows, or agent/MCP tooling into a real production environment.

Job Description

Senior Software Engineer responsible for designing, building, and maintaining high-performance, scalable backend services for the Enterprise Platform team. Serve as a senior individual contributor who can own production systems end-to-end and make an immediate impact with minimal direction. Design and develop data-intensive gRPC and REST APIs and backend services. Work primarily within a Go-based environment while contributing across other backend technologies as needed. Refactor and modernize legacy services, including migration of Node.js services to Go. Contribute to architecture decisions involving scalability, fault tolerance, performance, reliability, and cost. Own technical problems from design through implementation, testing, deployment, and production support. Use AI-assisted/agentic coding tools as part of the daily development workflow while maintaining strong engineering quality through testing, review, and validation. Provide technical leadership through architecture, execution, code reviews, mentoring, and engineering best practices. Operate autonomously within a lean engineering organization without heavy reliance on Product Owners or Project Managers. Help increase engineering velocity while bringing new ideas around AI-assisted development and technical innovation. Remote LATAM role supporting a distributed Enterprise Platform engineering team.