Overview

Onsite (New Delhi, India)

Responsibilities

• Be part of a cutting-edge AI company with an innovative team dedicated to transforming the recruitment and career development industry.
• Work in a fast-paced, mission-driven startup
• Collaborate with a global, diverse, creative, and forward-thinking team
• Drive meaningful impact on the future of careers
• This is a full-time hybrid role for an AI Engineer (LLM / Agents).
• The AI Engineer will be responsible for designing, developing, and deploying intelligent AI agents and LLM-powered systems that automate and enhance our career optimization features including autonomous resume analysis, intelligent job matching, AI interview agents, etc.
• We are looking for someone who is adept at building agentic AI systems and working with large language models, but also a great collaborator that can work with an asynchronous, remote team situated across the globe. Traditional Machine Learning experience is highly preferred.
• Lead and manage the development of autonomous AI agents that power our core features including intelligent resume optimization, ATS scanning agents, job matching systems, and AI-driven career coaching, AI Interview, etc.
• Design and implement multi-agent systems using frameworks like LangChain, AutoGen, CrewAI, or LangGraph for complex workflow orchestration
• Work closely with a team of 4+ engineers to integrate agentic AI capabilities across our web applications and Chrome browser extensions
• Develop and maintain RAG (Retrieval-Augmented Generation) systems for contextual career guidance and personalized recommendations
• Implement advanced prompt engineering strategies and fine-tuning techniques for domain-specific LLMs
• Build and optimize vector databases for semantic search and knowledge retrieval systems
• Design agent workflows that can autonomously handle multi-step career optimization tasks
• Collaborate with the Product and Design team to translate AI agent capabilities into intuitive user experiences
• Ensure scalability, reliability, and performance of AI agent systems in production environments
• Implement human-in-the-loop systems and agentic evals for agent oversight and quality control
• Drive integration of state-of-the-art LLMs (GPT-4, Claude, Gemini) and emerging AI technologies
• Work with big data technologies such as ClickHouse, BigQuery, etc. for training data management and LangSmith (or similar) for logging and tracing.
• Build traditional Machine Learning workflows, fine-tune models, etc. for non-LLM use cases.

Qualifications

• LLM Engineering, Agentic AI Frameworks (LangChain/AutoGen/CrewAI), Python, OpenAI APIs (or similar), Prompt Engineering, Vector Databases, Google Cloud Platform, Git, AI Product Experience, Firebase, Node Js, Clickhouse