Senior Data and AI Engineer

Intapp • Charlotte, NC

2d

About The Position

Intapp is hiring a senior engineer to build its data foundation and the governed AI services that run on it. The role owns pipelines from source to model using Python and dbt, deploys them with Docker and Kubernetes on AWS, and exposes trusted data to agents through Model Context Protocol (MCP) servers.

This is a hands-on role spanning traditional data engineering and applied AI. The engineer partners directly with business teams to turn requests into working solutions, operates production data and agentic systems, and helps establish standards for secure, reliable engineering. The role also includes reviewing code and mentoring engineers.

Requirements

• At least 8 years of professional data engineering experience, including a record of owning production systems end to end.
• Strong Python skills for data processing, automation, and services.
• Hands-on dbt experience with models, tests, macros, and deployment.
• Experience with Docker and Kubernetes to deploy, scale, and troubleshoot data workloads, as well as Git, CI/CD, and infrastructure as code.
• Solid AWS experience across core services for storage, compute, networking, and security.
• Advanced SQL skills and a sound understanding of data modeling, warehousing, and performance tuning.
• Practical Model Context Protocol knowledge, 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, and 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 Haves

• 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 their data quirks.
• Experience with retrieval-augmented generation, vector search, or LLM evaluation frameworks.

Responsibilities

• Design, build, and operate batch and incremental data pipelines in Python, using dbt for transformation, testing, and documentation; address issues at the source.
• Containerize workloads with Docker and run them on Kubernetes, using infrastructure as code and CI/CD to deploy safely and frequently.
• Build on AWS services for storage, compute, orchestration, and security, and tune systems for cost and performance.
• Design and build MCP servers and connectors that provide agents with governed access to enterprise data and tools.
• Deploy and operate production agentic workflows, including tool use, orchestration, evaluation, observability, and guardrails.
• Establish patterns for authentication, access control, and auditability, and evaluate AI techniques for their production value.
• Work with stakeholders to define problems, agree on outcomes, and deliver solutions in small, visible steps.
• Review code and mentor engineers, raising standards for design, testing, and documentation.

Benefits

• Professional development opportunities.
• Reimbursement for training and continuing education.
• Modern, open offices.
• Complimentary lunches and fully stocked kitchens.
• Wellness programs.
• Flexible time off.
• Benefits designed to care for employees and their families.
• Family-formation benefits and support during the family-building journey.
• Paid volunteer time off.
• Donation matching program.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior