AI Engineer / Developer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Aptino, is seeking the following. Apply via Dice today! Job Title AI Engineer / Developer Role Overview We are looking for an AI Data Engineer / Developer to design, build, and maintain scalable data pipelines and AI-ready data systems that power machine learning and generative AI applications. This role sits at the intersection of data engineering, software development, and AI, ensuring high-quality, reliable data flows from source to model deployment. You will work closely with data scientists, ML engineers, and product teams to transform raw data into structured, model-ready datasets and production-grade AI services. Key Responsibilities Data Engineering & Pipelines • Design, build, and maintain scalable data pipelines for structured and unstructured data • Ingest data from multiple sources (databases, APIs, streaming platforms, files, sensors) • Ensure data quality, validation, lineage, and versioning for AI/ML workloads • Optimize data storage and retrieval for performance and cost efficiency AI & Machine Learning Enablement • Prepare, transform, and feature-engineer datasets for ML and AI models • Support training, evaluation, and deployment of ML and LLM-based systems • Build and maintain data pipelines for model retraining and monitoring • Integrate vector databases and embedding pipelines for AI search and RAG systems Development & Systems • Develop reusable data and AI services using Python and/or other relevant languages • Build APIs and microservices to serve data and AI outputs • Collaborate on CI/CD pipelines for data and ML workflows • Monitor, debug, and improve production data and AI systems Collaboration & Governance • Work closely with data scientists, ML engineers, and product teams • Implement data governance, security, and compliance best practices • Document architectures, pipelines, and processes clearly Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience) • Strong experience with Python and data engineering frameworks • Experience building ETL/ELT pipelines and working with large datasets • Solid understanding of databases (SQL and NoSQL) and data modeling • Familiarity with machine learning workflows and AI concepts • Experience with cloud platforms (AWS, Azure, or Google Cloud Platform) Preferred / Nice-to-Have Skills • Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) • Knowledge of LLM ecosystems (OpenAI, Hugging Face, LangChain, etc.) • Experience with vector databases (Pinecone, FAISS, Weaviate, Milvus) • Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) • Experience with MLOps tools and practices • Understanding of data privacy, security, and compliance standards