Junior Ai Native Engineer

Experteer Overview In this role you design, build, and ship production-grade software that integrates AI at the core of development.You will work across the full stack to connect applications with agentic AI backends and enterprise AI pipelines, collaborating with client teams.You’ll apply AI to the full software lifecycle, from testing to debugging and delivery, driving measurable productivity and quality improvements.This position offers a direct path to advanced engineer programs and cross-industry exposure, in a dynamic AI-native environment.Compensaciones / Beneficios- Use AI coding assistants daily to boost productivity and output quality- Integrate LLM APIs into production applications, manage token limits and latency, and build abstraction layers- Apply AI across the software delivery lifecycle, including AI-generated tests, debugging, code review, and prompt engineering- Own the quality and production-readiness of AI-generated outputs, evaluating reliability and failure modes- Define and track KPIs for AI-assisted workflows and present metrics to stakeholders- Own end-to-end delivery in Agile sprints alongside client engineering teams- Contribute to shared knowledge bases, reusable components, and internal AI tooling standards- Build and integrate application layers and interfaces that connect full-stack systems to agentic backendsResponsabilidades- Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field- Commercial software engineering experience in production environments or equivalent- Proficiency in Python, Java, or TypeScript- Hands-on experience using AI tools in day-to-day engineering work, including calling LLM APIs in production- Basic understanding of web technologies (JavaScript, HTML, CSS)- Familiarity with cloud fundamentals (AWS, Azure, or GCP), Docker, and CI/CD- Understanding of Agile delivery fundamentals- Experience with SQL or NoSQL databases- Ability to validate AI outputs and understand AI limitations and responsible use- Familiarity with agentic system concepts and orchestration frameworks (LangChain, LangGraph, or equivalent); production experience preferredRequisitos principales- vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams- structured AI certification pathways- clear development track toward agentic and forward-deployed engineering

Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field

• Commercial software engineering experience in production environments or equivalent
• Proficiency in Python, Java, or TypeScript
• Hands-on experience using AI tools in day-to-day engineering work, including calling LLM APIs in production
• Basic understanding of web technologies (JavaScript, HTML, CSS)
• Familiarity with cloud fundamentals (AWS, Azure, or GCP), Docker, and CI/CD
• Understanding of Agile delivery fundamentals
• Experience with SQL or NoSQL databases
• Ability to validate AI outputs and understand AI limitations and responsible use
• Familiarity with agentic system concepts and orchestration frameworks (LangChain, LangGraph, or equivalent); production experience preferredRequisitos principales
• vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams
• structured AI certification pathways
• clear development track toward agentic and forward-deployed engineering