About the Role
We are seeking a hands-on AI Engineer to design, build, integrate, and deploy intelligent AI agents for conversational and autonomous experiences. The role involves agent design, orchestration, tool integrations, evaluation, production deployment, and continuous optimization. You will collaborate closely with AI product managers, data scientists, backend engineers, and business stakeholders to translate requirements into scalable AI solutions.
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Key Responsibilities and Skills
AI Agent Development & Orchestration
- Design and deploy LLM-powered agents that reason, plan, retrieve information, and execute actions.
- Build multi-agent systems with orchestrators, supervisors, and specialized agents; implement tool calling, handoffs, delegation, and multi-step execution.
- Develop context management, conversational memory, session management, guardrails, fallbacks, and human-in-the-loop workflows.
- Develop both digital and voice-enabled agents.
- Integrate OpenAI, Azure OpenAI, Anthropic, and other LLM providers.
- Maintain a deep understanding of speech models and their different architectures.
- Support Arabic and English experiences.
- Optimize accuracy, latency, reliability, and token costs.
RAG and Semantic Retrieval
- Develop system prompts, structured outputs, and RAG solutions grounded in enterprise data.
- Build KB ingestion and retrieval pipelines.
- Gain hands-on experience with vector databases, including Pinecone and open search.
Tool Development & Enterprise Integrations
- Build REST APIs, webhooks, and Model Context Protocol (MCP) integrations for enterprise systems.
- Implement secure authentication, authorization, and session handling.
- Enable business actions such as product discovery, recommendations, bookings, and transactions.
Agent Evaluation, Testing & Optimization
- Build automated evaluations for task completion, tool selection, accuracy, and response quality.
- Maintain test datasets for edge cases and multi-turn conversations; run regression tests.
- Debug execution traces, tool calls, and context propagation; monitor production quality, latency, and costs.
Production Deployment & Engineering Excellence
- Build maintainable production services with logging, monitoring, observability, and tracing.
- Support CI/CD, code reviews, unit tests, documentation, and secure development.
- Troubleshoot production incidents and integration or performance issues.
Technical Skills
- Strong hands-on Python, backend/API development, and asynchronous programming skills.
- Proven delivery of LLM applications and AI agents, using at least one of LangGraph/LangChain, Kore.ai, OpenAI Agents SDK, Semantic Kernel, or CrewAI.
- Strong understanding of orchestration, tool calling, context, memory, and structured LLM workflows.
- Experience with REST APIs, microservices, RAG, embeddings, and vector databases such as Pinecone or Azure AI Search.
- Working knowledge of Git, Docker, CI/CD, cloud deployment, and LLM debugging.
- Familiarity with voice and text conversational AI, STT/TTS, and real-time architectures.
Requirements
Professional Experience
- 5+ years of software or AI engineering experience, including at least one production-grade agentic AI or LLM application.
- Experience integrating AI solutions with enterprise systems and external APIs.
- Strong independent problem-solving skills and end-to-end delivery ownership.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or a related field.
Preferred Qualifications
- Experience with Kore.ai Artemis or a similar enterprise agent platform.
- MCP server/client development and agent-to-agent communication knowledge.
- Familiarity with Azure cloud and enterprise AI deployment.
- Knowledge of LLM evaluation and observability tools such as LangSmith or Langfuse.
Ideal Candidate
A builder, not just an AI enthusiast: someone who has personally written agent code, implemented tools, debugged LLM behavior, and deployed AI applications. You should be comfortable owning orchestration, APIs, context management, and production troubleshooting.
