Rackspace Technology

AI Engineer Trainee – Software approach

Rackspace Technology

full-time

Posted on:

Location Type: Remote

Location: Vietnam

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Job Level

Entry Level

Tech Stack

AirflowAWSAzureCloudDockerMicroservicesPythonSQL

About the role

  • Assist in building the "connectors" between LLMs and real-world data tools (Airflow, dbt, Microsoft Fabric).
  • Help develop validation layers to ensure AI-generated code (SQL/Python) is syntactically correct and follows governance standards.
  • Support the implementation of multi-step reasoning cycles (Plan-Act-Observe) using frameworks like LangGraph or CrewAI.
  • Work with Azure Functions and Container Apps to deploy and scale AI-driven microservices.
  • Build automated test suites to benchmark agent performance and detect regressions in reasoning.

Requirements

  • Strong Software Engineering Foundation: * Proficient in Python (focus on clean code, modularity, and error handling).
  • Solid understanding of Data Structures, Algorithms, and OOP.
  • Comfortable with Git workflows and RESTful API consumption.
  • Hands-on experience calling LLM APIs (OpenAI, Anthropic, or Azure AI).
  • Practical understanding of Agentic AI concepts: How agents use tools, memory, and self-correction.
  • Knowledge of Structured Outputs (Pydantic/JSON schemas) to make AI outputs machine-readable.
  • Good command of SQL. You should be able to write and debug complex queries manually before trying to automate them with AI.
  • Education: Final year student or recent graduate in CS, Software Engineering, or related fields.
  • Experience with Docker or basic Cloud infrastructure (Azure/AWS).
  • Familiarity with Asynchronous Programming in Python (asyncio).
  • Contribution to open-source projects or a strong GitHub portfolio showing clean software design.
  • Engineering Rigor: You care about edge cases, latency, and system reliability, not just "cool" AI demos.
  • Problem-First Mindset: You look for the best engineering solution, even if it sometimes means not using AI.
  • High Learnability: You can read a technical API doc or a new AI research paper and translate it into working code quickly.
Benefits
  • Mentorship from Senior Engineers on building production-grade Agentic systems.
  • Exposure to the Azure AI Foundry ecosystem and enterprise-level DataOps.
  • A chance to be at the forefront of the shift from "Chat" to "Autonomous Agents.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
PythonSQLData StructuresAlgorithmsObject-Oriented ProgrammingAsynchronous ProgrammingGitRESTful APIDockerAgentic AI
Soft Skills
Engineering RigorProblem-First MindsetHigh Learnability