Data Engineer and AIML

URGENT HIRING AI Engineer (Agentic AI & Azure Data Engineering)

Company: Honeybee Tech Solutions Pvt. Ltd.
Project: Enterprise Hydrocarbon Inventory (HYD-INV)
Client: Chevron

Job Summary

We are looking for an experienced AI Engineer with strong Azure Data Engineering and Agentic AI expertise to build and deploy AI-powered agents that accelerate data product development, pipeline engineering, testing, reconciliation, analytics, and visualization.

The role goes beyond traditional AI/ML development. Candidates must have hands-on experience with Azure data technologies such as Azure Databricks, PySpark, Azure Data Factory, and Unity Catalog, along with practical experience in Generative AI, Large Language Models (LLMs), and agentic workflows.

Key Responsibilities

1. Agentic AI & LLM Engineering

• Design, develop, and deploy AI-powered agents using Azure AI Foundry and Azure OpenAI.
• Build agentic workflows using frameworks such as LangChain and Semantic Kernel.
• Implement Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
• Develop multi-agent orchestration workflows to automate data discovery, development, testing, and reconciliation.
• Implement LLM evaluation frameworks and responsible AI controls.
• Develop AI-powered chatbots and self-service business insight capabilities.

2. Azure Data Engineering

• Develop and optimize data pipelines using Azure Databricks, PySpark, SQL, and Azure Data Factory.
• Work with Delta Lake and Unity Catalog for data management, governance, and access control.
• Design scalable ETL/ELT pipelines and enterprise data models.

3. Analytics & Visualization

• Enable AI-assisted development of analytics and visualization solutions.
• Work with Power BI to develop and support data-driven reporting.

4. Software Engineering & DevOps

• Build and maintain reusable services, REST APIs, and microservices.
• Use GitHub for version control and collaborative development.
• Implement CI/CD pipelines, automated testing, and DevOps best practices.

5. Data Governance & Quality

• Implement data lineage, metadata management, and data quality frameworks.
• Support governed data discovery and enterprise data marketplace capabilities.

6. Stakeholder Collaboration

• Collaborate with Product Owners, Data Engineers, Data Analysts, Solution Architects, and business stakeholders.
• Support the delivery of trusted, governed, and AI-ready enterprise data products.

Required Technical Skills

AI & Agent Engineering

• Azure AI Foundry
• Azure OpenAI
• Agentic AI frameworks
• LangChain
• Semantic Kernel
• Retrieval-Augmented Generation (RAG)
• LLM evaluation frameworks
• Multi-agent orchestration

Azure Data Engineering

• PySpark
• SQL
• Azure Databricks
• Delta Lake
• Unity Catalog
• Azure Data Factory (ADF)
• Data modeling
• ETL/ELT pipeline design

Analytics & Visualization

• Power BI

Software Engineering

• GitHub
• CI/CD
• REST APIs
• Microservices
• DevOps

Data Governance

• Data lineage
• Metadata management
• Data quality frameworks

Ideal Candidate Profile

• Strong hands-on experience in Azure Data Engineering and modern data platforms.
• Practical experience building LLM-powered applications and agentic AI workflows.
• Strong Python, SQL, and problem-solving skills.

Interested candidates are requested to share their updated CV for evaluation.

Thanks & Regards,
P Deva
Talent Acquisition Manager
Honeybee Tech Solutions Pvt. Ltd.