Senior Software Engineer

MUST BE ABLE TO WORK ON-SITE @ LEAST 2-3 DAYS A WEEK IN TOWSON, MD

NO 3RD PARTIES. WE CANNOT SPONSOR VISAS

At Curio Wellness we empower people to thrive by adapting plant nature to human nature. We are committed to transforming the conversation around cannabis, fostering a deeper understanding of its benefits, and ensuring that every product we offer meets the highest standards.

We are looking for a Full Stack Data, Application & AI Engineer to build and integrate the data platforms, applications, and AI-powered capabilities that will drive Curio’s next stage of growth.

This is a true end-to-end engineering role blending:

• AI/ML enablement & integration
• Data governance & data quality engineering

You will design and build the pipelines, cloud infrastructure, internal apps, and AI-ready governed data foundation needed to power analytics, automation, and next-generation business intelligence.

Please note: This position involves working with plant material, which may include exposure to pollen, allergens, and other plant-related substances.
We recommend that applicants with known plant allergies or sensitivities consult with a healthcare professional before applying for this position.

include the following. Other duties may be assigned.

• Design, build, andmaintainscalable data pipelines and system integrations (ETL/ELT).
• Develop and enhance the enterprise data warehouse/lake house, including schemas, dimensional models, and performance tuning.
• Implement automated data validation, testing, andmonitoringto ensure reliability and trustworthiness.

• Build andmaintaininternal applications, dashboards, and tools that expose data and AI capabilities to end users.
• Build secure, modular back-end services (APIs, microservices) supporting internal workflows and analytics.
• Develop intuitive front-end interfaces using modern frameworks.
• Integrate applications with enterprise systems, cloud services, and external platforms.

• Prepare and structure datasets to support AI/ML training, inference, and deployment.
• Partner with analytics and business teams to deploy models into production applications or automated processes.
• Build pipelines, services, andmonitoringto support model lifecycle management.
• Integrate LLM-based capabilities into internal tools, workflows, or end-user applications where applicable.

• Implement andmaintaindata governance standards, including naming conventions, metadata, lineage, and access controls.
• Ensure data accuracy, consistency, and completeness across systems byestablishingvalidation rules, profiling, and automated checks.
• Partner with business owners to define data definitions, ownership, and stewardship for key entities and metrics.
• Build andmaintainrole-based access and data security policies in accordance with compliance requirements.
• Promote a culture of trusted data by ensuring that all analytics, applications, and AI models use governed, high-quality data.

• Write clean, maintainable, thoroughly tested code;participate in code reviews and design critiques.
• Use CI/CD pipelines and best Dev Ops practices for automated build, testing, and deployment.
• Implement secure engineering practices:secrets management, encryption, least-privilege access, and audit logging.
• Set up monitoring, observability, and alerts for data pipelines, applications, and model endpoints.

• Translate business requirements into technical designs, user stories, or prototypes.
• Work with product, operations, finance, and retail to understand needs and deliver scalable solutions.
• Break complex work into iterative deliverables andparticipatein Agile ceremonies.
• Contribute to internal standards, documentation, and engineering best practices.

• 5+ years across software engineering and/or data engineering roles.
• Strong experience with Python, SQL, and at least one modern back-end framework.
• Experience building end-to-end web applications (front-end + back-end + database).
• Cloud platform experience (AWS preferred, Azure/GCP ok).
• Proven experience building data pipelines, data models,…