Sr AI Engineer (Backend & Platform)
New
J
JobgetherTrucking and fleet compliance
Based in Brazil; work from anywhere in Latin America, Availability to overlap with US Eastern business hours, approximately 9 AM–5 PM.Full-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Advanced written and spoken English, as the role operates entirely in English.
- Required Skills
- AWSPythonKubernetesTypeScriptAzureTerraform
Requirements
- Bring a strong backend or full-stack software engineering background and recent hands-on AI engineering experience.
- Have delivered AI agents or LLM-powered features to production that real users actively rely on.
- Be able to own the production lifecycle, including Terraform-based infrastructure as code, CI/CD, deployment, and monitoring.
- Have experience with AWS and/or Azure, including Kubernetes, ECS, or Azure-equivalent container orchestration.
- Use evaluations and data to determine deployment readiness and measure production agent performance.
- Have strong proficiency in Python or TypeScript and practical experience with LLM APIs and MCP.
- Be familiar with agent frameworks or SDKs and able to determine when a framework is unnecessary.
- Have established experience using coding agents as the primary approach to software development.
- Work independently, gather requirements from non-technical stakeholders, communicate clearly, and provide specific, honest answers.
- Have advanced written and spoken English.
- Be available to overlap with US Eastern business hours, approximately 9 AM–5 PM.
- Be willing to participate in hands-on technical interviews, including detailed discussions of systems and solutions previously built and shipped.
Responsibilities
- Design, build, and deploy AI agents from initial requirements through production release.
- Deliver early iterations and improve solutions based on feedback from real users.
- Collaborate with product, support, and engineering stakeholders to translate business challenges into technical requirements.
- Own AI-agent infrastructure and delivery, including infrastructure as code, CI/CD pipelines, and deployments.
- Monitor production systems, evaluate agent performance, manage costs, and address failures.
- Establish best practices in agentic engineering to improve team productivity and delivery quality.
- Use coding agents to define tasks, review generated code, validate outcomes, and coordinate parallel workflows.
- Strengthen development processes through testing, CI, agent reviews, and reusable skills.
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