Cynet Health is hiring a Senior AI Prompt Engineering Lead to architect, govern, and optimize high-fidelity Large Language Model systems at the intersection of Agentic AI and Hiring Automation. This systems engineering role focuses on designing the cognitive architecture for autonomous recruitment, evaluation, and interaction systems.

What You'll Do

Engineer production-grade prompt infrastructures for workflows like candidate evaluation, resume parsing, interview automation, and stakeholder communication.
Deploy advanced prompting paradigms like Chain-of-Thought, 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 adherence to hiring rubrics.
Build and manage stateful, multi-agent workflows using LangGraph and LangChain.
Design complex, multi-step decision trees incorporating human-in-the-loop checkpoints, autonomous error recovery, and conditional branching.
Optimize execution paths for latency and token cost without compromising analysis depth or system reliability.
Architect Retrieval-Augmented Generation (RAG) pipelines for high-fidelity context injection and minimal hallucinations.
Manage integration with vector databases and implement advanced retrieval strategies like semantic re-ranking, query expansion, and context compression.
Define and implement automated evaluation frameworks (LLM-as-a-Judge) for regression testing and measuring output drift.
Make strategic decisions regarding model routing and the viability of fine-tuning versus context-window optimization.
Establish strict documentation standards for prompt versioning and reproducibility for enterprise-grade compliance.

What We're Looking For

Extensive hands-on experience with LangChain and LangGraph.
Mastery of prompt engineering for frontier models like GPT-4o, Claude 3.5 Sonnet, and Gemini 1.5 Pro.
Proven track record of deploying independent AI applications within HR Tech, Recruitment Automation, or Workflow Orchestration.
Ability to conceptualize and build end-to-end AI systems and integrated cognitive architectures.
Bachelor’s or Master’s degree in Computer Science, AI, or a related discipline.
Proven experience leading AI projects, particularly in prompt engineering.
Strong portfolio or case studies showcasing 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.

Nice to Have

B.Tech/M.Tech from top-tier institutes (IITs, IIITs, BITS, or equivalent global institutions).
Experience operating in high-velocity, product-first startup environments.
Experience with OpenAI Assistants API and Function Calling.
Familiarity with LLM observability platforms like LangSmith, Weights & Biases, or PromptLayer.
Expertise in adversarial prompting and security hardening for LLMs.