Rackspace - AI Engineer Trainee (Software-approach)
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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. • Data Literacy: 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. • Preferred/Nice-to-have • 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. • Traits We Look For • 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. • Traits We Look For
Responsibilities
• System Integration: Assist in building the "connectors" between LLMs and real-world data tools (Airflow, dbt, Microsoft Fabric). • Reliable Execution: Help develop validation layers to ensure AI-generated code (SQL/Python) is syntactically correct and follows governance standards. • Agentic Workflows: Support the implementation of multi-step reasoning cycles (Plan-Act-Observe) using frameworks like LangGraph or CrewAI. • Infrastructure Support: Work with Azure Functions and Container Apps to deploy and scale AI-driven microservices. • Evaluations as Code: Build automated test suites to benchmark agent performance and detect regressions in reasoning. • 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. • We are looking for a Software-focused Trainee who treats AI as a powerful tool in their engineering toolkit. Instead of just "prompting," you will help us build the robust software systems that allow AI Agents to execute SQL, manage dbt models, and interact with data pipelines reliably.
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