Job Summary
We are seeking a skilled AI & Data Engineer to design, develop, and maintain scalable data pipelines, cloud-based data platforms, and AI-powered applications. The ideal candidate will have a strong background in Python, SQL, ETL/ELT processes, cloud technologies, machine learning, and Generative AI.
The candidate will be responsible for building reliable data infrastructure, preparing high-quality datasets, and developing AI/ML solutions that support business intelligence, advanced analytics, and intelligent automation.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
- Build data ingestion, transformation, and processing solutions using Python and SQL.
- Develop and optimize data warehouses, data lakes, and cloud-based data platforms.
- Work with AWS, Azure, or Google Cloud Platform for data engineering and AI workloads.
- Develop and deploy machine learning models and AI-powered applications.
- Implement Generative AI solutions using Large Language Models (LLMs), prompt engineering, and Retrieval-Augmented Generation (RAG).
- Work with AI/ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Utilize Apache Spark, PySpark, and workflow orchestration tools such as Apache Airflow.
- Work with Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
- Integrate AI models and data services using REST APIs and cloud-native technologies.
- Implement data quality checks, model monitoring, and performance optimization.
- Collaborate with data scientists, software engineers, and business stakeholders to deliver scalable solutions.
- Follow best practices for data security, governance, model reliability, and deployment automation.
Required Technical Skills
- Strong proficiency in Python and SQL.
- Experience with data engineering, ETL/ELT pipelines, and data transformation.
- Knowledge of Machine Learning, Deep Learning, and AI application development.
- Understanding of Generative AI, LLMs, RAG, and prompt engineering.
- Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.
- Familiarity with Apache Spark, PySpark, and data orchestration tools.
- Experience with data warehouses such as Snowflake, Databricks, Redshift, or BigQuery.
- Knowledge of REST APIs, Git, CI/CD, and Docker.
- Understanding of data modeling, database design, and scalable data architectures.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
- Experience with vector databases such as Pinecone, FAISS, or Weaviate.
- Familiarity with LangChain, LlamaIndex, and AI agent development.
- Experience with MLOps, MLflow, and AI model deployment.
- Knowledge of streaming technologies such as Apache Kafka.
- Experience building production-grade AI solutions integrated with enterprise data platforms.
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Candidates must be authorized to work in the United States without current or future employer sponsorship.