AI Data Engineer at Weekday AI

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

2500000.0

Posted On

14 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

LangChain, Python, SQL, Azure Cloud Services, Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure Databricks, Azure Cognitive Services, Azure Machine Learning, NLP, Spark, Scala, Power BI, MLOps, Agile Methodologies

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Salary range: Rs 1200000 - Rs 2500000 (ie INR 12-25 LPA) Min Experience: 5 years Location: Pune JobType: full-time We are looking for an experienced AI Data Engineer to work at the intersection of data engineering and advanced AI technologies. In this role, you will act as a key liaison between business stakeholders and technical teams, translating complex business requirements into scalable data and AI-driven solutions. You will leverage Python, LangChain, Azure Cloud services, and agentic AI technologies to build intelligent, persona-based and execution agents while managing high-impact data products for internal stakeholders. Key Responsibilities Design and build persona-based and execution agents using Python and LangChain. Develop a deep understanding of enterprise data assets and evaluate their suitability for diverse internal use cases. Act as a primary point of contact for data consumers, managing change requests and communicating updates effectively. Collaborate with business and IT stakeholders to gather, analyze, and document complex data and AI requirements. Perform detailed data analysis to assess feasibility and align solutions with available datasets. Translate business requirements into clear technical specifications and support Agile delivery with engineering teams. Represent stakeholder needs throughout the data lifecycle, working with data acquisition, modeling, and platform teams. Support validation and testing of data and AI solutions to ensure alignment with business expectations. Produce analytical insights and reports using statistical methods, programming, and visualization tools. Implement and manage Azure Cloud components including authentication, AKS, and Azure AI Services. Integrate MCP tools and deploy AI models into data pipelines using Azure Machine Learning and MLOps practices. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Information Technology, Mathematics, or a related field. 5+ years of experience as a Data Engineer in large-scale or Big Data environments. Strong expertise in Python and advanced SQL for complex data analysis. Hands-on experience with Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, and Azure Databricks. Familiarity with Azure Authentication, Azure Kubernetes Service (AKS), and managed AKS environments. Understanding of Azure Cognitive Services and Azure Machine Learning. Foundational knowledge of Generative AI and Agentic AI, including LLMs, NLP, and transformer-based models. Experience with prompt engineering, model fine-tuning, and AI model deployment using MLOps or containerized frameworks. Awareness of Responsible AI practices such as bias detection, explainability, and ethical AI principles. Strong experience working in Agile delivery environments. Excellent written and verbal communication skills with the ability to collaborate in global teams. Why This Role Work hands-on with cutting-edge AI and data engineering technologies. Exposure to large-scale, enterprise-grade data and AI platforms. Strong opportunities for long-term growth and technical leadership. Skills LangChain, Python, SQL, Azure Cloud Services, Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure Databricks, Azure Cognitive Services, Azure Machine Learning, NLP, Spark, Scala, Power BI, MLOps, MCP Tools Integration, Agile Methodologies

Responsibilities

The AI Data Engineer will design and build persona-based and execution agents using Python and LangChain, while collaborating with stakeholders to translate complex requirements into data-driven solutions. They will also manage high-impact data products and support validation and testing of AI solutions.