Senior Data and AI Engineer

Charlotte, NC (onsite)

IntApp is building governed data and AI capabilities that teams can trust. This role focuses on end-to-end ownership of data pipelines and AI services, from source ingestion through transformation and deployment, with secure access to enterprise data via MCP servers.

What you’ll work on

• Design, build, and operate batch and incremental pipelines in Python, using dbt for transformation, testing, and documentation, including fixing issues at the source.
• Containerize data workloads with Docker and run them on Kubernetes, using infrastructure as code and CI/CD to ship safely and frequently.
• Build on AWS for storage, compute, orchestration, and security, while tuning for both cost and performance.
• Design and build MCP servers and connectors that provide agents governed access to enterprise data and tools.
• Deploy and operate agentic workflows in production, covering tool use, orchestration, evaluation, observability, and guardrails.
• Set patterns for authentication, access control, and auditability, and evaluate new AI techniques so only effective approaches reach production.
• Partner with stakeholders to define the problem, align on outcomes, and deliver progress in small, visible increments.
• Review code and mentor engineers to raise standards for design, testing, and documentation.

What you bring

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

Nice to have

• Orchestration experience with Airflow or a comparable 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, including common data quirks.
• Experience with retrieval-augmented generation, vector search, or LLM evaluation frameworks.

Benefits and support

• Comprehensive wellness and flexible time off programs
• Family-formation benefits and support
• Reimbursement for training and continuing education
• Complimentary lunches and fully stocked kitchens
• Paid volunteer time off
• Donation matching program

Technologies: Python, dbt, Docker, Kubernetes, AWS, Git, CI/CD, infrastructure as code, SQL, Model Context Protocol (MCP), LLMs, Airflow, Redshift, Snowflake, BigQuery