Find & Apply For Artificial Intelligence Engineer Jobs in Vero Beach, Florida

Find the signal in the data. Cruz Street delivers AI-ready data, fast, and we're looking for a hands-on data engineer to help. This is a contract-to-hire role. It starts at about 20 hours a week and has a clear path to full-time as we grow. You'll be based in the Vero Beach area and join the team at our headquarters for in-person collaboration; the rest of the work is remote and deliverable-based. You'll build production AWS and Azure data pipelines for Cruz Street clients and help ship DashProphet 2.0, our SaaS analytics product.

Pay:

starting at $75/hour (1099), negotiable based on experience and fit.

If converted to full-time:

starting at $115,000 base plus benefits (healthcare, PTO, 401k). About Cruz Street Cruz Street helps organizations use data science to acquire customers, make smarter decisions, and accelerate growth. We were founded in New York in 2018 and are now headquartered in Vero Beach, Florida. We're an AWS QuickSight Service Delivery Partner delivering data engineering, analytics and BI, AI and data science, and enterprise software on AWS and Microsoft Azure. Our clients include media and advertising, healthcare and life sciences, associations and standards organizations, SaaS, financial services, and retail and CPG. We also build our own product, DashProphet, which takes users from data to dashboards in minutes; version 2.0 adds AI-enabled features. What you'll work on Client solutions: governed pipelines and analytics-ready models across our industry verticals.

SaaS and embedded analytics:

the pipelines behind branded, embedded analytics. DashProphet 2.0: multi-tenant ingestion, curated lakehouse models, and the data foundations for AI features.

Context Warehouse and QuickSight Hub:

Cruz Street offerings that make client data AI-ready.

AI and data science enablement:

data for forecasting, segmentation, and AI use cases.

Reusable accelerators:

shared connectors, ingestion frameworks, and CI/CD templates. Key responsibilities Build connectivity to data sources via REST APIs, SFTP, and database/file integrations, handling auth, pagination, rate limiting, and incremental loads. Ingest into an S3-based lake/lakehouse (raw/staged/curated zones, Parquet/Iceberg, Glue Data Catalog). Develop ETL/ELT in Python and PySpark on AWS Glue, loading curated data into Redshift and RDS. Model data in Redshift (dimensional models, stored procedures, tuning) and enable ad hoc access through Athena. Build QuickSight datasets and dashboards, including SPICE and row-level security for multi-tenant use. Orchestrate with Step Functions, EventBridge, and Lambda, with monitoring, alerting, and data quality checks. Prepare pipelines and features for AI capabilities (Amazon Bedrock, SageMaker, embeddings/vector stores). Contribute to infrastructure-as-code and CI/CD (CDK/CloudFormation or Terraform; GitHub Actions or CodePipeline). Troubleshoot production issues and perform root cause analysis. Join client requirements sessions, write clear documentation, and estimate your own work. Required qualifications 5+ years of cloud data engineering across AWS and Azure. 5+ years of Python data engineering. 5+ years engineering advanced data solutions: APIs/integrations (REST, SFTP); pipelines (AWS Glue, Azure Data Factory); lakes, lakehouses and warehouses (Redshift, Azure Synapse); RDBMS (Amazon RDS, Azure SQL). Strong SQL, including data modeling for analytics and query optimization. 1+ year of agentic AI engineering: planning, building, deploying, and maintaining agentic applications. Working knowledge of Git, CI/CD, and collaborative development. Clear written and verbal communication; comfortable working directly with clients. Preferred qualifications AWS or Azure certifications (Solutions Architect, DevOps Engineer, Data Engineering, or AI/ML such as AWS Generative AI Developer - Professional, ML Engineer - Associate, Azure AI Engineer Associate).

AI/ML data workloads:

Bedrock, SageMaker, OpenSearch vector search, or Azure OpenAI/AI Search, including RAG, embeddings, and vector databases. Multi-tenant SaaS data platforms or embedded analytics. Apache Iceberg, Lake Formation, or other open table formats and governance. Consulting or client-facing delivery. Regulated data (e.g., HIPAA) and data security best practices. What we offer Work spanning client delivery and product engineering, including shipping AI features in a live SaaS product. Direct mentorship from senior AWS architects on a small team where your work is visible. Support for AWS certifications and training. A contract rate starting at $75/hour, negotiable based on experience and fit, and a path to a full-time salaried role with benefits. How to apply Apply here with your resume and a short note describing a pipeline you built end to end: the sources, the services you used, and the outcome. Please include your AWS or Azure certification IDs or Credly links. Cruz Street is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of any protected characteristic.

Pay:

From $75.00 per hour Expected hours: 20.0 per week

Benefits:

Flexible schedule Professional development assistance Application Question(s): Are you able to work on a 1099 contract basis for about 20 hours per week, with a path to full-time? Have you built and deployed an agentic AI application in production? Briefly describe it and one data pipeline you built end to end (sources, services, outcome).

Experience:

AWS data engineering: 5 years (Required) Azure data engineering: 5 years (Preferred) Ability to

Commute:

Vero Beach, FL 32960 (Required)

Work Location:

Hybrid remote in Vero Beach, FL 32960