Founding AI Engineer

India·NoidaFull-timemid

Machine Learning EngineerData

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Overview

This role is for one of Weekday’s clientsSalary range: Rs 3000000 - Rs 9000000 (ie INR 30 - 90 LPA) Min Experience: 6+ yearsLocation: NCR,

Technical Tools

Machine Learning EngineerData

~1 min read

Proven experience building and deploying production-grade Agentic AI systems, beyond basic chatbots or conventional RAG applications.
Strong expertise in LLM orchestration, multi-step tool calling, and autonomous agent workflows.
Hands-on experience with MCP servers, structured outputs, and context management.
Practical experience developing browser automation and computer-use agents using Playwright and CDP.
Strong Python backend engineering skills, including experience with asyncio and frameworks such as FastAPI or Django.
Understanding of agent architecture, persistent memory, asynchronous workflows, and failure-recovery mechanisms.
Experience with AI evaluation and observability tools such as Langfuse and OpenTelemetry.
Familiarity with LLM-as-a-Judge, trajectory logging, agent tracing, and regression testing.
Hands-on experience deploying scalable applications on AWS, including services such as ECS, SQS, Celery, and CloudWatch.
Knowledge of CI/CD practices and production infrastructure management.
Strong problem-solving skills and the ability to independently own technical architecture and execution.

~1 min read

Design, develop, and deploy production-grade LLM agents capable of executing complex, multi-step tasks.
Implement advanced agent workflows involving multi-step tool calling, MCP servers, structured outputs, and context management.
Build robust LLM orchestration systems that enable agents to plan, reason, execute, and verify task outcomes.

Develop browser and computer-use agents using Playwright and Chrome DevTools Protocol (CDP).
Build automation capabilities for interacting with third-party websites, authentication flows, logins, and dynamic web interfaces.
Ensure reliable execution of complex workflows across external platforms.

Design persistent memory systems and asynchronous task execution frameworks.
Implement scheduling, retries, state management, and failure-recovery mechanisms.
Build reliable workflows that can manage long-running tasks and handle unexpected execution failures.

Implement outcome verification, agent tracing, and trajectory logging.
Develop evaluation frameworks using LLM-as-a-Judge and regression testing.
Monitor agent performance, identify failure patterns, and continuously improve reliability and execution quality.

Build scalable backend services and distributed agent systems using Python.
Design and deploy cloud-based infrastructure on AWS.
Ensure system performance, scalability, reliability, and maintainability in production environments.

A hands-on AI engineer who has built and operated autonomous agents in real-world production environments.
Comfortable working across the entire AI engineering stack, from agent architecture and orchestration to backend development and cloud deployment.
Experienced in building reliable systems that interact with external platforms and execute multi-step workflows.
Strong ownership mindset with the ability to make technical decisions and drive projects independently.
Comfortable working in a fast-paced startup environment and collaborating directly with founders.