About
Location: Remote - India Employment Type: Full-time Experience: Mid-Level to Senior-Level
About the Role
We are looking for a Data Engineer with a strong interest in Agentic AI and Generative AI systems. In this role, you will design and build scalable data infrastructure, develop intelligent data pipelines, and enable AI agents and LLM-powered applications to access, process, and reason over enterprise data efficiently. The ideal candidate combines strong data engineering fundamentals with hands-on experience in modern AI technologies and cloud-native systems.
Key Responsibilities Design, build, and maintain scalable data pipelines for structured and unstructured data. Develop ETL/ELT workflows that support analytics, machine learning, and AI-driven applications. Build data platforms that power Agentic AI systems, Retrieval-Augmented Generation (RAG), and LLM-based workflows. Integrate enterprise data sources with AI agents, APIs, vector databases, and semantic search systems. Implement data quality, governance, monitoring, and observability practices across the data ecosystem. Collaborate with software engineers, AI engineers, product teams, and stakeholders to deliver production-ready solutions. Optimize data architectures for performance, reliability, scalability, and security. Support deployment and orchestration of AI-powered data workflows in cloud environments. Contribute to technical design reviews, architecture discussions, and best-practice initiatives. Required Qualifications
Strong experience in Data Engineering with Python and SQL. Experience building and maintaining ETL/ELT pipelines. Familiarity with data orchestration and workflow tools. Experience working with cloud platforms such as AWS, Azure, or GCP. Understanding of data modeling, distributed systems, and modern data architectures. Knowledge of APIs, data integration patterns, and scalable backend systems. Experience working with databases, data lakes, and data warehouses. Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications
Experience with Large Language Models (LLMs), Generative AI, and Agentic AI concepts. Familiarity with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar orchestration tools. Experience building Retrieval-Augmented Generation (RAG) pipelines. Knowledge of vector databases and semantic search systems. Exposure to Docker, Kubernetes, CI/CD pipelines, and cloud-native deployment practices. Understanding of MLOps, LLMOps, monitoring, and evaluation frameworks. Experience developing data platforms that support AI-powered applications. Desired Traits
Passion for emerging AI technologies and intelligent systems. Strong communication and collaboration skills. Ability to translate business requirements into scalable technical solutions. Continuous learner with a builder mindset and focus on practical outcomes. What You'll Gain
Opportunity to work on cutting-edge Agentic AI and Generative AI solutions. Exposure to modern data engineering and AI infrastructure challenges. Collaborative environment focused on innovation and rapid iteration. Professional growth through ownership of impactful projects and emerging technologies.
Languages
- English
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