Senior Data and AI Engineer

Location: Hybrid in Charlotte, NC, United States; partially remote.

Company

hirify.global is a growing public company offering a modern, connected, and flexible work environment focused on professional growth, well-being, collaboration, and innovation.

What you will do

• Design, build, operate, and troubleshoot batch and incremental data pipelines in Python, using dbt for transformation, testing, and documentation.
• Containerize and deploy workloads with Docker and Kubernetes, using infrastructure as code and CI/CD.
• Build and optimize AWS-based storage, compute, orchestration, and security solutions.
• Design MCP servers and connectors that provide governed access to enterprise data and tools, and deploy agentic workflows with tool use, orchestration, evaluation, observability, and guardrails.
• Establish authentication, access control, and auditability patterns while evaluating new AI techniques for production use.
• Partner with business stakeholders, deliver incremental solutions, review code, and mentor engineers.

Requirements

• 8+ years of professional data engineering experience, including ownership of production systems end to end.
• Strong Python skills for data processing, automation, and services, plus hands-on dbt experience with models, tests, macros, and deployment.
• Experience with Docker and Kubernetes for deploying, scaling, and troubleshooting data workloads, together with Git, CI/CD, and infrastructure as code.
• Solid AWS experience across core storage, compute, networking, and security services.
• Advanced SQL and a strong understanding of data modeling, warehousing, and performance tuning.
• Practical Model Context Protocol experience, including building, deploying, or integrating MCP servers or similar LLM tool interfaces.
• Experience building or deploying agentic workflows involving orchestration, tool calling, evaluation, and monitoring, with the judgment to distinguish useful AI patterns from hype.
• Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.

Nice to have

• Experience with Airflow or a comparable orchestration tool.
• Experience with a cloud data warehouse such as Redshift, Snowflake, or BigQuery.
• Familiarity with enterprise source systems such as CRM, ERP, and finance platforms.
• Experience with retrieval-augmented generation, vector search, or LLM evaluation frameworks.

Culture & Benefits

• Professional development opportunities with reimbursement for training and continuing education.
• Modern open offices with complimentary lunches and fully stocked kitchens.
• Wellness programs, flexible time off, and family-formation benefits.
• Paid volunteer time off and donation matching.
• Collaborative, welcoming, and flexible work environment focused on growth and well-being.

Hiring process

• The interview process generally consists of three or more virtual or in-person meetings.