AI Engineer / Developer

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