Job Opportunities API

About Mindera At Mindera, we build high-performing, cross-functional teams that solve complex business challenges through technology. We partner with global clients to deliver innovative, scalable, and cloud-native solutions while fostering a collaborative engineering culture built on autonomy, ownership, and continuous learning. We are looking for a Data Engineer with strong expertise in Generative AI data pipelines, Vector Databases, AWS, and modern data engineering technologies to help build next-generation AI-powered platforms. This role will focus on developing scalable pipelines for Large Language Model (LLM) applications, Retrieval-Augmented Generation (RAG), and Voice AI solutions. Role Overview As a Data Engineer (Generative AI & Vector Systems) , you will be responsible for designing and building scalable data pipelines that prepare, transform, and index enterprise data for AI applications. You will work closely with AI Engineers, Data Scientists, Machine Learning Engineers, and Software Engineers to enable high-performance semantic search and retrieval systems using Vector Databases and cloud-native technologies. This is an exciting opportunity to work on cutting-edge Generative AI solutions involving embeddings, vector search, RAG architectures, and large-scale cloud data processing. Requirements Key Responsibilities AI Data Engineering Design and develop scalable data ingestion pipelines for AI and ML applications. Build automated pipelines to clean, transform, chunk, enrich, and load enterprise data into Vector Databases. Create efficient workflows for generating embeddings from structured and unstructured data. Optimize data quality for semantic search and retrieval systems. Vector Database Engineering Design and manage Vector Database architectures. Optimize indexing, storage, metadata management, and retrieval performance. Improve similarity search performance and retrieval latency. Work with embedding models and vector search optimization techniques. Data Pipeline Development Develop production-grade ETL/ELT pipelines. Build batch and near real-time ingestion pipelines. Automate workflow orchestration using Apache Airflow. Monitor pipeline performance and ensure high availability. Cloud Data Engineering Develop cloud-native solutions on AWS. Work with services such as: Amazon S3 AWS Glue EMR Lambda Athena IAM CloudWatch Optimize compute resources for large-scale AI workloads. SQL & Data Processing Write complex SQL queries across distributed data sources. Use Starburst/Trino to federate and query multiple data platforms. Design efficient data models for AI workloads. Perform large-scale joins and transformations. AI & Machine Learning Support Work closely with AI engineers to support LLM-based applications. Build Retrieval-Augmented Generation (RAG) pipelines. Manage embedding generation and vector indexing. Support prompt engineering and retrieval optimization initiatives. Performance & Reliability Improve data pipeline performance and scalability. Implement monitoring, logging, and alerting. Troubleshoot production data issues. Ensure data integrity and governance. Required Technical Skills Programming Python (Advanced) SQL (Advanced) Data Engineering ETL / ELT Data Transformation Data Cleansing Data Chunking Strategies Metadata Management Data Modeling Vector Databases Hands-on experience with one or more: Pinecone Milvus Qdrant Chroma Weaviate (Good to have) FAISS (Good to have) Workflow Orchestration Apache Airflow Cloud Strong experience with AWS services: Amazon S3 AWS Glue Amazon EMR Lambda Athena IAM CloudWatch Query Engines Experience with: Starburst Trino Presto (Good to have) AI / Machine Learning Working knowledge of: Large Language Models (