AI Data Engineer

About the job:Key responsibilities:

1. Work with LangChain, LangGraph, Agno, and MCP (Model Context Protocol).

2. Assist in building AI Agents and Agentic AI workflows.

3. Integrate APIs, tools, and external data sources with AI applications.

4. Work with time-series data, forecasting, and predictive analytics.

5. Work with basic ML algorithms such as Random Forest and XGBoost.

6. Assist in developing forecasting and predictive models.

7. Analyze datasets and identify patterns and trends. Who can apply:Only those candidates can apply who:have minimum 1 years of experienceare from Mumbai onlyare Computer Science Engineering studentsSalary:₹ 4,00,000 - 8,00,000 /yearExperience:1 year(s)Deadline:[hidden]:59:59Skills required:Python, SQL, Machine Learning, Artificial intelligence, NumPy, Pandas, Generative AI Development, Machine Learning Operations (MLOps) and XGBoostOther Requirements:1. Freshers with relevant AI/ML/Data Engineering projects, internships, or strong Python skills can apply.2. Time-series forecasting and prompt engineering.3. Basic knowledge of Machine Learning.About Company:Anvenssa AI is a global AI startup headquartered in the UK with operations in India, dedicated to revolutionizing the e-commerce landscape through intelligent automation. Our focus is on building an AI Agentic Network tailored for the D2C (Direct-to-Consumer) market, helping online brands, particularly Shopify store owners, automate customer support and sales processes with cutting-edge AI agents.

With a dynamic 15-member team of innovators, engineers, and growth specialists, Anvenssa AI delivers scalable, multilingual, 24/7 solutions that reduce human resource dependency, boost operational efficiency, and enhance customer engagement across channels. Our mission is to empower enterprises and SMEs with AI automation.

Responsibilities

Key responsibilities:

1. Work with LangChain, LangGraph, Agno, and MCP (Model Context Protocol).

2. Assist in building AI Agents and Agentic AI workflows.

3. Integrate APIs, tools, and external data sources with AI applications.

4. Work with time-series data, forecasting, and predictive analytics.

5. Work with basic ML algorithms such as Random Forest and XGBoost.

6. Assist in developing forecasting and predictive models.

7. Analyze datasets and identify patterns and trends.