AI Engineer – Job Description
Position Summary
We are seeking an innovative AI Engineer to design, develop, test, and deploy AI-powered solutions that drive business value through automation, advanced analytics, and intelligent applications.
The AI Engineer will collaborate with cross-functional teams to build and test scalable machine learning and generative AI solutions that enhance operational efficiency and improve customer experiences.

Key Responsibilities
• Design, develop, test, and deploy AI/ML and Generative AI solutions to solve complex business problems.
• Build and optimize data pipelines to support AI model training and inference.
• Develop and integrate Large Language Model (LLM) applications, AI agents, and Retrieval-Augmented Generation (RAG) solutions.
• Create scalable APIs and AI services for enterprise applications.
• Test agentic solutions and validate outputs to ensure accuracy, reliability, and expected behavior.
• Collaborate with data engineers, software developers, and business stakeholders to translate requirements into AI solutions.
• Evaluate, fine-tune, and monitor AI models for accuracy, performance, and reliability.
• Implement MLOps best practices for model deployment, testing, monitoring, and lifecycle management.
• Ensure AI solutions comply with enterprise security, governance, and responsible AI standards.
• Stay current with emerging AI technologies and recommend innovative approaches.

Required Qualifications
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Strong programming skills in Python and SQL.




• Experience with Large Language Models (OpenAI, Anthropic, Llama, etc.) and prompt engineering.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with REST APIs, Git, and software development best practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications
• Experience with Snowflake, Databricks, or up-to-date data platforms.
• Knowledge of vector databases, semantic search, and RAG architectures.
• Experience with AI orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.
• Familiarity with Docker, Kubernetes, and CI/CD pipelines.
• Experience developing AI-powered analytics dashboards using Streamlit.

Preferred Technical Skills
• Python SQL Machine Learning & Deep Learning Generative AI & Large Language Models (LLMs) Prompt Engineering RAG & Vector Databases Snowflake, Databricks Azure REST APIs & Microservices Git, Docker, Kubernetes Power BI, Tableau, Streamlit Agentic AI testing and output validation Success Measures Deliver scalable AI solutions that improve business outcomes.
• Automate manual processes through AI-driven workflows. Improve model accuracy, performance, and reliability.
• Successfully test agentic workflows and validate outputs against expected results.
• Partner effectively with stakeholders to translate business needs into AI capabilities.
• Continuously evaluate and adopt emerging AI technologies to drive innovation.

Skills
Databricks, Snowflake, Agentic AI, RAG, MLOps, Machine Learning, Generative AI, Power BI, SQL, Python, Vector Databases

📌 AI Data Engineer (Chennai)
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