Software Engineer, AWS, Backend Developer

MUST LIVE IN THE BALTIMORE, MD AREA - WE CANNOT PROVIDE SPONSOR SHIPS

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 Junior Full Stack & Dev Ops Engineer to help build, integrate, and operate the data platforms, internal applications, and cloud infrastructure that power Curio’s analytics, automation, and AI capabilities. This is a hands‑on growth role for an early‑career engineer who enjoys working across the stack and is excited to build deep skills in Dev Ops and cloud operations.

You will write application and pipeline code, and you will also help keep our build, deployment, and monitoring systems running reliably—learning alongside senior engineers who will mentor you throughout. We are an AI‑forward engineering team in two senses. We use AI tools every day to write, review, and ship code faster, and we build AI and LLM‑powered capabilities into the products and platforms we deliver.

We are looking for someone who is genuinely excited to work this way and to help shape how Curio puts AI to work. You will contribute to:
Full stack application and API development, Data pipeline and integration support, CI/CD, cloud infrastructure, and deployment automation, Monitoring, observability, and operational reliability, AI‑augmented engineering and AI/LLM‑powered features.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Help build, maintain, and improve CI/CD pipelines for automated build, testing, and deployment.
• Assist with provisioning and managing cloud infrastructure (AWS preferred), increasingly using infrastructure‑as‑code.
• Support containerized workloads (Docker) and assist with orchestration on ECS, Kubernetes, or serverless platforms.
• Set up and maintain monitoring, logging, alerting, and dashboards for applications, pipelines, and services.
• Help respond to operational issues, participate in troubleshooting, and document runbooks and fixes.
• Apply secure engineering practices: secrets management, least privilege access, and audit logging.

• Build and maintain internal applications, dashboards, and tools under guidance from senior engineers.
• Develop back‑end services (APIs, microservices) and front‑end interfaces using modern frameworks.
• Integrate applications with enterprise systems, cloud services, and external platforms.
• Help integrate AI and LLM‑powered features—chat, summarization, search, automation—into internal tools and user‑facing applications.

• Help build and maintain data pipelines and system integrations (ETL/ELT).
• Support the enterprise data warehouse/lakehouse, including schema changes and basic performance tuning.
• Assist with automated data validation, testing, and monitoring to keep data reliable and trustworthy.
• Help prepare and structure data so it is AI‑ready, supporting model inputs, retrieval, and LLM‑powered features.

• Write clean, maintainable, tested code; participate in code reviews and design discussions.
• Use AI‑assisted coding tools to work faster, while applying sound judgment to review, test, and verify generated code.
• Follow data governance and security standards, including naming conventions, access controls, and data quality checks.
• Translate requirements into small, iterative deliverables and participate in Agile ceremonies.
• Contribute to internal documentation, standards, and engineering best practices.

Required

• 1–3 years of experience in software engineering, data engineering, Dev Ops, or a related role (internships, co‑ops, and strong project work count).
• Working knowledge of Python and SQL.
• Exposure to building web applications (front‑end, back‑end, and database).
• Some hands‑on experience with Dev Ops fundamentals:
  Git, CI/CD pipelines, and basic cloud services.
• Familiarity with at least one cloud platform (AWS preferred, Azure/GCP ok).
• Understanding basic data governance, data quality, and secure access concepts.
• Comfort using…