Description

You will design and maintain production-level AI systems, focusing on LLMs, agents, and complex automation frameworks. You own the end-to-end development lifecycle, from building REST services to deploying scalable cloud infrastructure.

Responsibilities

• Build and optimize production AI systems using Python, leveraging libraries like Pandas and NumPy for data processing.
• Develop and integrate Large Language Models (LLMs), agents, and automation frameworks using TensorFlow, PyTorch, LangGraph, or LangChain.
• Design and implement RESTful APIs using Java and Spring Boot to connect AI agents to external systems.
• Manage CI/CD pipelines and containerized deployments using Kubernetes, Docker, and Jenkins within a DevSecOps environment.
• Deploy and monitor AI workloads on Amazon Web Services (AWS), ensuring reliability and performance.

Required Skills

• 7+ years of experience building production-level AI or ML systems, specifically with LLMs, agents, or automation.
• 7+ years of professional Python development, including experience with Pandas or NumPy.
• Hands-on experience with Deep Learning frameworks: TensorFlow and PyTorch.
• Practical knowledge of AI agent orchestration tools such as LangGraph or LangChain.
• Experience with Natural Language Processing (NLP) concepts and Reinforcement Learning (RL).
• Proficiency in Java and Spring Boot for developing REST services.
• Strong understanding of the Software Development Lifecycle (SDLC) and DevSecOps practices.
• Experience administering CI/CD pipelines using Kubernetes, Docker, or Jenkins.
• Operational experience with Amazon Web Services (AWS).

Preferred Skills

• Familiarity with automated testing tools for AI system maintenance and validation.
• Experience collaborating on code using GitHub or similar platforms.

Key Skills

Education

Any Graduate