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.
- Robust 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