Job Description
Location: Remote / Dehradun (Hybrid options available) Engagement Model: Part-time / Contractual Time Commitment: 8–10 Hours / Week Role Mandate We are soliciting applications for a Senior AI Prompt Engineering Lead to architect, govern, and optimize high-fidelity Large Language Model (LLM) systems. This role is positioned at the intersection of Agentic AI and Hiring Automation , requiring a sophisticated approach to building systems that recruit, evaluate, and interact with human talent autonomously. This is not a content generation role; it is a systems engineering role . You will be responsible for designing the cognitive architecture of our platform, utilizing frameworks such as LangChain and LangGraph to build deterministic, scalable, and reasoning-capable agents for production environments. Core Responsibilities 1. Advanced Prompt Architecture & Cognitive Modeling Strategic Design: Engineer production-grade prompt infrastructures for complex workflows, including candidate evaluation, resume parsing, interview automation, and autonomous stakeholder communication. Methodology Implementation: Deploy advanced prompting paradigms—including Chain-of-Thought (CoT), Tree-of-Thought, Self-Consistency, and Instruction Hierarchies—to ensure high-precision reasoning. Constraint Engineering: Architect robust guardrails and instruction-following protocols to maintain system safety, prevent jailbreaks, and ensure strict adherence to hiring rubrics. 2. Agentic AI & Workflow Orchestration System Construction: Build and manage stateful, multi-agent workflows using LangGraph and LangChain . Decision Logic: Design complex, multi-step decision trees that incorporate human-in-the-loop (HITL) checkpoints, autonomous error recovery, and conditional branching. Operational Efficiency: Optimize execution paths for latency and token cost without compromising the depth of analysis or system reliability. 3. RAG & Knowledge-Grounded Systems Pipeline Engineering: Architect Retrieval-Augmente
