We are seeking a motivated AI & Data Engineer with 2–3 years of experience to join our innovative team. This role sits at the intersection of data engineering, cloud analytics, and applied AI, where you’ll design scalable data pipelines while also enabling LLM-powered applications and machine learning workflows.
In this position you will collaborate closely with data scientists, ML engineers, and product teams to transform raw data into intelligent insights, AI-driven features, and production-ready LLM solutions.
Key Responsibilities
Data Engineering & Analytics
- Design, build, and optimize ETL pipelines using Apache Airflow
- Build and maintain Snowflake data warehouses for scalable ingestion, transformation, and analytics
- Develop data workflows for structured and semi‑structured data using AWS services
- Integrate data from APIs, databases, and cloud storage using Python
- Implement data quality checks, monitoring, and validation frameworks
- Design and document data models to support analytics and ML workflows
- Document pipeline architectures, schemas, and best practices
AI, ML & LLM Enablement
Collaborate with data scientists and ML engineers to prepare datasets for AI / ML training and inferenceSupport LLM-powered applications, including :Prompt engineering and optimizationFine‑tuning LLMs (instruction tuning, domain adaptation)Managing embeddings, vector databases, and retrieval pipelinesBuild data pipelines to support RAG (Retrieval‑Augmented Generation) workflowsDevelop Streamlit applications for data exploration, AI demos, and internal toolsAssist in deploying and monitoring AI / ML pipelines in production environmentsRequired Qualifications
2–3 years of professional experience in Data Engineering, AI Engineering, or a related roleStrong hands‑on experience with Apache AirflowPractical experience with AWS services (S3, Lambda, Glue, EC2, or similar)Experience working with Snowflake for data warehousingStrong Python skills for data processing, automation, and API integrationExperience building data apps or dashboards using StreamlitSolid understanding of data modeling and ETL designWorking knowledge of AI / ML workflows, especially data preparationFamiliarity with LLMs, including :Prompt engineeringFine‑tuning or adapting LLMsWorking with embeddings and vector storesBachelor’s degree in Computer Science, Data Engineering, AI, or equivalent experiencePreferred Qualifications
Advanced experience with AWS data and ML servicesDeep expertise in Snowflake performance tuning and optimizationExperience building complex Streamlit applicationsAdvanced Python skills for large‑scale data wranglingExperience with LLM fine‑tuning, evaluation, and deploymentFamiliarity with LangChain, LlamaIndex, or similar LLM frameworksKnowledge of Airflow best practices for scalable pipeline designExperience with AI / ML model deployment and monitoring#J-18808-Ljbffr