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Lead (Agentic AI)

Raya · Egypt

About Raya

18 open jobs

Strong hiring record · median 41 days open

100100

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Lead (Agentic AI) at Raya. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

  • Translate business needs into workflows, choosing deterministic automation, single-agent, or multi-agent designs based on reliability, complexity, cost, and value.
  • Build modular, tested Python services that integrate large language models (LLMs), APIs, databases, and enterprise tools into production-ready applications.
  • Implement agent orchestration, including tool calling, structured outputs, state, memory, routing, retries, timeouts, and human approval steps, to ensure reliable agent behavior.
  • Build retrieval-augmented generation (RAG) pipelines covering ingestion, chunking, embeddings, reranking, and access-aware retrieval to improve knowledge grounding and accuracy.
  • Establish evaluation datasets and automated tests for task completion, accuracy, retrieval quality, tool selection, safety, latency, and cost.
  • Own deployment readiness, CI/CD, observability, versioning, and rollback, and lead incident investigation to ensure reliable production operation.
  • Implement security and governance controls, including least privilege access, PII protection, secrets management, audit trails, and prompt-injection defenses, to safeguard enterprise AI systems.
  • Mentor the team, review code and architecture, and set standards for testing, modularization, and documentation to strengthen team capability.
  • Define acceptance criteria and benchmark models and frameworks for quality, portability, and total cost to guide product and technology decisions.
  • Educational Background:
  • Relevant degree in Computer Science or a related field, or equivalent practical experience.
  • Experience:
  • 7+ years of experience in software engineering, machine learning engineering, or applied AI, including demonstrated ownership of an LLM-powered production application from architecture through operation.
  • 3-4 years of experience in mentoring engineers and guiding a multidisciplinary team.
  • Technical Proficiency:
  • Strong Python skills, with experience in APIs, asynchronous processing, typed data models, automated testing, and Git
  • Practical experience with agent workflows, tool/function calling, structured outputs, and retrieval-augmented generation (RAG)
  • Understanding of LLM limitations, including hallucinations, context constraints, and nondeterministic behavior
  • Experience with SQL, data pipelines, and vector search or other retrieval systems
  • Experience with Docker, CI/CD, cloud deployment, monitoring, and production troubleshooting
  • Familiarity with LangGraph, LangChain, Semantic Kernel, or equivalent agent tooling and Model Context Protocol (MCP) integrations.

Skills

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