Requirements
• 3+ years of professional experience in AI engineering, machine learning engineering, applied AI, or related roles.
• Currently working at a product-based company.
• Previous experience being part of a founding or early-stage engineering team, preferably having taken a product from 0 to 1.
• Hands-on experience building and running production-grade LLM agents, including multi-step tool calling, MCP servers, context management, memory, structured outputs, and streaming.
• Experience building browser or computer-use agents using Playwright, CDP, or similar technologies.
• Experience building agent evaluation and observability systems, including trajectory logging, replayable runs, LLM-as-judge scoring, and regression testing.
• Solid Python skills, including experience with asyncio and frameworks such as FastAPI or Django.
• Production experience with AWS, including ECS, SQS or Celery workers, autoscaling, CloudWatch, and CI/CD.
• High ownership, high agency, and the ability to work independently in an early-stage startup environment.
• Open to working in-office in Gurgaon six days a week.
• Genuinely interested in joining a startup and building products from zero to one. Responsibilities
• Own the architecture and development of AI agents that can take user requests and complete multi-step tasks independently.




• Build and improve the agent harness, including tool calling, MCP servers, memory, context management, and structured outputs.
• Develop browser and computer-use agents capable of completing real-world tasks across third-party websites, including login flows, OTP verification, and dynamic pages.
• Build intelligent workflows that can recover from failures, handle incomplete tasks, and verify whether an action has actually been completed.
• Design and implement scheduling systems that can keep tasks running across multiple days and resume execution when required.
• Build evaluation frameworks to measure agent performance, reliability, and accuracy.
• Establish observability through trajectory logging, replayable runs, LLM-as-judge scoring, and regression testing.
• Work on improving agent performance using real-world task outcomes and feedback.
• Work directly with the founders to make critical technical and product decisions.
• Take complete ownership of AI systems, from initial architecture to production deployment and scaling. Job Details Gurgaon (In-office, 6 days a week) Interview Process
• Technical Screening
• AI/LLM Engineering Round
• System Design Round
• Founders' Round
• Culture Fit Round

📌 Artificial Intelligence Engineer (Gurugram)
🏢 ClanX
📍 Gurugram