AI Prompt Engineering Lead – Agentic AI, Hiring Automation

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🕒 February 25

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Cynet Group

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2010

🎯 Recruiter

🤝 B2B

Recruitment • Healthcare • B2B

Cynet Group is a global workforce solutions leader and parent company to Cynet Health, Cynet Systems, Cynet Locums, and Cynet Canada. The company specializes in staffing and workforce optimization across healthcare, technology, government, and professional services, providing travel nursing, allied health, physician/advanced practice placements, IT and professional staffing, and locum services. Cynet emphasizes data-driven staffing strategies, 24/7 recruiting support, and scalable enterprise staffing solutions to connect organizations with skilled professionals worldwide.

📋 Description

• Engineer production-grade prompt infrastructures for complex workflows, including candidate evaluation, resume parsing, interview automation, and autonomous stakeholder communication. • Deploy advanced prompting paradigms—including Chain-of-Thought (CoT), Tree-of-Thought, Self-Consistency, and Instruction Hierarchies—to ensure high-precision reasoning. • Architect robust guardrails and instruction-following protocols to maintain system safety, prevent jailbreaks, and ensure strict adherence to hiring rubrics. • Build and manage stateful, multi-agent workflows using LangGraph and LangChain. • Design complex, multi-step decision trees that incorporate human-in-the-loop (HITL) checkpoints, autonomous error recovery, and conditional branching. • Optimize execution paths for latency and token cost without compromising the depth of analysis or system reliability. • Architect Retrieval-Augmented Generation (RAG) pipelines that ensure high-fidelity context injection, minimizing hallucinations through rigorous source attribution. • Manage integration with vector databases (Pinecone, Weaviate, Chroma) and implement advanced retrieval strategies such as semantic re-ranking, query expansion, and context compression. • Define and implement automated evaluation frameworks (LLM-as-a-Judge) to conduct regression testing on prompts and measure output drift. • Make strategic decisions regarding model routing (GPT-4 vs. Claude vs. Gemini) and determine the viability of PEFT/LoRA fine-tuning versus context-window optimization. • Establish strict documentation standards for prompt versioning and reproducibility to ensure enterprise-grade compliance.

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, AI, or related discipline. • Proven experience leading AI projects, particularly in prompt engineering. • Strong portfolio or case studies showcasing your work in AI and recruitment automation. • Understanding of user-centered design principles and how to apply them in AI settings. • Experience collaborating with cross-functional teams to deliver successful AI applications.