Principal Engineer (AI Systems)

Description

Key Responsibilities

• Design and code RAG systems with embeddings, hybrid search, and evaluation pipelines.
• Develop hands-on multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI, or custom).
• Implement and maintain LLMOps pipelines for prompt versioning, cost tracking, and evaluation.
• Integrate AI workflows with backend services and data layers for real-world scalability.
• Experiment with LLMs for retrieval, summarization, and personalization use cases.
• Contribute directly to code, architecture reviews, and performance improvements.

Skills, Knowledge and Expertise

• 5+ years of backend or ML engineering experience, with strong Python coding skills.
• Proven experience shipping RAG systems (vector DBs, embeddings, chunking).
• Familiarity with orchestration frameworks (LangGraph, LangChain, AutoGen, or similar).
• Understanding of LLM behavior, evaluation, and fine-tuning workflows.
• Experience with APIs, microservices, and cloud-native development (AWS preferred).

• Experience with unstructured data (PDFs, tables, images).
• Familiarity with distributed systems concepts (async, message queues, caching).
• Experience with LLM evaluation or reinforcement learning from feedback (RLAIF).
• Understanding of data versioning or retrieval metrics.

• Builder mindset — thrives on writing, debugging, and improving production code.
• Collaborative, humble, and open to feedback.
• Strong communicator who explains design decisions clearly.

About Emumba