AI Engineer Casera

AI / Data Engineer

About the Role

Were seeking a highly skilled AI/Data Engineer to design build and optimize data pipelines machine learning infrastructure and intelligent applications that turn complex data into actionable insights. Youll collaborate closely with data scientists ML engineers and software developers to deploy scalable production-ready AI systems and ensure data quality observability and performance across the stack.

Key Responsibilities

• Design and implement robust data ingestion and transformation pipelines (batch and streaming) using tools such as Airflow Spark Databricks or AWS Glue.
• Develop and maintain ETL/ELT workflows for structured and unstructured data from multiple sources (APIs event streams databases third-party services).
• Collaborate with data scientists to operationalize ML models including feature engineering model serving and real-time inference pipelines.
• Deploy monitor and maintain machine learning models using MLflow SageMaker Vertex AI or similar frameworks.
• Implement MLOps best practices including CI/CD for model retraining versioning and testing.
• Optimize performance and scalability of data storage solutions (e.g. Redshift BigQuery Snowflake or Delta Lake).
• Ensure data quality lineage and governance through monitoring validation and documentation.
• Contribute to infrastructure-as-code (IaC) setups for reproducible deployments using Terraform CDK or CloudFormation.
• Collaborate with cross-functional teams to support AI-driven analytics dashboards and decision intelligence applications.

Qualifications

• Bachelors or Masters degree in Computer Science Data Engineering or a related field. 5 years of experience in data engineering ML engineering or backend systems. Strong programming skills in Python SQL Scala Java or any OP languages. Proficiency with cloud platforms (AWS GCP or Azure) and their data/AI services. Experience with ML pipelines including feature stores model registries and inference APIs.
• Familiarity with containerization and orchestration (Docker Kubernetes). Solid understanding of data modeling warehousing and schema design.
• Knowledge of modern AI frameworks (PyTorch TensorFlow scikit-learn) and vector databases (Pinecone Weaviate FAISS) is a plus.
• Understanding of data privacy security and compliance (HIPAA GDPR SOC 2) preferred.

Nice to Have

• Experience implementing LLM-powered systems (e.g. retrieval-augmented generation embeddings prompt optimization).
• Knowledge of real-time analytics and event-driven architectures (Kafka Kinesis Pub/Sub).
• Familiarity with observability stacks (Prometheus Grafana OpenTelemetry). Contributions to open-source or AI research projects.

What We Offer

• Opportunity to build scalable AI systems that drive measurable business impact. Collaborative environment working alongside data scientists ML researchers and software engineers.
• Flexible hybrid/remote work culture.
• Competitive compensation benefits and growth opportunities.