Join SourceBae as a Senior Data Software Engineer to build scalable data pipelines, intelligent services, and advanced data retrieval solutions using Python, Azure, and large language models.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Senior Data Software Engineer – ML & AI Data Platform
Experience: 7 – 12 Years
Shift Timing: 7:00 AM – 4:00 PM IST
Job Type: Full Time - Remote/Hybrid
Position Overview
We are looking for a Senior Data Software Engineer with strong expertise in Machine Learning and modern data architectures to join an AI-driven data platform initiative. The role involves building scalable data pipelines, intelligent services powered by large language models, and advanced data retrieval solutions.
Technology Stack
- Python
- Azure Infrastructure
- Azure AI Services
- ETL Pipelines
- Serverless Microservices
- Vector Databases
- Knowledge Graphs
- Retrieval Augmented Generation (RAG)
- Large Language Models (LLMs)
- Prompt Engineering
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Responsibilities
- Develop and maintain scalable ETL pipelines for structured and unstructured data.
- Design and implement serverless microservices using cloud-native patterns.
- Build and optimize data solutions using vector databases and knowledge graphs.
- Collaborate with ML engineers to integrate large language model capabilities into production systems.
- Implement Retrieval Augmented Generation (RAG) pipelines for advanced AI use cases.
- Work with Azure AI Services to deliver reliable and scalable solutions.
- Ensure code quality through testing, code reviews, and adherence to engineering standards.
- Collaborate with distributed teams and participate in technical discussions across time zones.
Requirements
- 7+ years of experience in Data Engineering.
- 7+ years of experience building ETL pipelines.
- 7+ years of experience with Python development.
- 3+ years of experience with Azure AI Services.
- 2+ years of experience with Retrieval Augmented Generation (RAG).
- Hands-on experience with ETL pipeline design and implementation.
- Familiarity with Azure infrastructure and cloud-native services.
- Understanding of microservices architecture and serverless computing.
- Experience working with vector databases and data indexing solutions.
- Knowledge of knowledge graphs and Retrieval Augmented Generation concepts.
- Experience integrating or working with large language models.
- Practical experience with prompt engineering.
- English proficiency sufficient for daily communication in an international team.
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Nice to Have
- Experience with Azure AI Services in production environments.
- Exposure to distributed system design and scalability patterns.
- Knowledge of data governance and data quality practices.
- Experience working in globally distributed teams.
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