Job Summary
We are representing a client in the F&B industry who is looking for a talented Lead Agentic AI Engineer to join their team.
Job Description
Agent Architecture & Orchestration
- Multi-Agent Ecosystems: Design and deploy architectures where specialized AI agents (e.g., Customer Facing Agent, Kitchen Expeditor Agent, Inventory Agent) seamlessly collaborate and communicate to execute complex restaurant operations.
- Agent Directing: Define the rules of engagement, conflict resolution, and delegation protocols between multiple autonomous agents.
- Tool Integration: Equip agents with the ability to safely interact with real-world restaurant environments (POS systems, payment gateways, kitchen display systems, and supplier APIs).
Context, Memory & Harness Engineering
- Memory Systems: Build robust state management and memory pipelines (short-term, long-term, semantic, and episodic) so agents remember VIP customers, ongoing complex orders, and shifting daily menus.
- Context Engineering: Design dynamic prompt architectures and retrieval-augmented generation (RAG) pipelines to ensure agents always have the exact context they need without hallucinating or exceeding token limits.
- Harness Engineering: Develop advanced evaluation harnesses and guardrails to ensure agents behave safely, reliably, and predictably in a live, fast-paced F&B environment.
Leadership & AgentOps
- Strategic Vision: Define the roadmap for our autonomous restaurant agent, transitioning from assisted AI features to full autonomy.
- AgentOps & Observability: Build monitoring systems to track agent performance, tool-call failure rates, memory degradation, latency, and token economics.
- Team Leadership: Lead and mentor a team of software engineers to build the infrastructure that supports your agentic vision.
Job Requirements
- Note: Deep hands-on experience training traditional ML models (e.g., TensorFlow, PyTorch) is NOT required for this role. We are looking for an applied AI/LLM orchestrator.
- Experience: 5+ years of software engineering experience, with a proven track record of building production-grade LLM applications or agentic workflows.
- Agentic Frameworks: Strong familiarity with multi-agent orchestration tools and frameworks (e.g., OpenClaw, LangChain, LlamaIndex, Semantic Kernel).
- Core AI Competencies: Deep understanding of Context Engineering (advanced prompting, context window optimization, RAG).
- Expertise in Memory Management (Vector databases like Pinecone, Weaviate, or Milvus, and knowledge graphs).
- Strong Harness Engineering skills (building sandboxes, evaluation loops, and deterministic guardrails for probabilistic models).
- Software Engineering: Proficiency in Python, Go, or TypeScript, and experience building robust API integrations to connect AI with physical/digital systems.
- Bonus Points: Experience in POS, retail tech, F&B operations, or e-commerce systems.
- Familiarity with event-driven architectures (Kafka, webhooks) to trigger agent workflows.
- No need for visa sponsorship.
- 3+ years of work experience with Context Engineering.
GET IN TOUCH
- Apply: [Confidential Information]
- WhatsApp: wa.me/6282137682541
