Job Description
We are seeking a Senior AI Engineer with practical experience in LLMs, LangChain or similar frameworks, and Retrieval-Augmented Generation (RAG) systems. In this role, you will help design and deploy intelligent, secure, and scalable AI solutions that enhance Zscaler’s products and internal automation tools.
The position emphasizes AI backend development and orchestration using Python, cloud deployment (AWS preferred, GCP optional), and integration of LLM-based services with light front-end development for chat interfaces, copilots, and dashboards.
Qualifications
Must-Have
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Solid working experience with Python for AI service development, API integration, and data processing.
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Practical hands-on experience with LangChain, RAG pipelines, or similar developer frameworks.
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Familiarity with LLM integration, prompt design, and embedding-based retrieval.
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Experience deploying applications on AWS (preferred) or GCP, particularly with EKS, ECS, or Cloud Run.
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Proficiency with Docker, Kubernetes, and cloud-native service orchestration.
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Experience building RESTful or GraphQL APIs for AI and data services.
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Understanding of cloud security, scalability, and performance optimization
principles.
Good-to-Have
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Experience developing conversational UIs, copilots, or AI-enabled dashboards (e.g., Slack apps, chat widgets).
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Familiarity with React, Next.js, or TypeScript for front-end feature integration.
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Exposure to Hugging Face Transformers, LlamaIndex, or LangGraph ecosystems.
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Knowledge of vector databases and data pipeline management.
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Understanding of compliance, privacy, and responsible AI practices in enterprise environments.
Education & Experience
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Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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Typically 4–8 years of experience in software or AI engineering, including 2+ years of hands-on experience with LLMs, LangChain, or RAG systems.