AI Integrations Engineer

Nozomi Networks

19h•$139,600 - $175,883•Remote

About The Position

Nozomi Networks is seeking an AI Integrations Engineer to develop the essential connections that enable business users to maximize the value of the company's AI tool stack. This role involves collaborating with users across various business functions to create advanced agentic solutions. The engineer will be responsible for ensuring these agents have secure access to company systems, clean data from the data warehouse, well-designed APIs, and a scalable Google Cloud-based architecture. This is a critical position where integrations built can be reused across numerous agents and users. The role requires close collaboration with data, security, and platform teams, and the engineer will serve as the primary expert for business users encountering limitations with no-code agents.

Requirements

5+ years of professional software or data engineering experience
Strong data engineering skills including SQL, dimensional modeling, ETL/ELT pipelines, and experience with a modern cloud data warehouse (e.g., BigQuery, Snowflake, Databricks, or Redshift)
Hands-on integration experience with at least one major CRM and one major ERP, including their APIs, data models, and specific characteristics
Proficiency with Google Cloud services such as Cloud Run or Cloud Functions, Apigee or API Gateway, Secret Manager, Cloud IAM, and BigQuery, Dataflow, or Cloud Data Fusion
Strong programming skills in Python and/or TypeScript
Experience designing and shipping REST APIs for consumption by other teams or systems
Solid understanding of authentication and authorization patterns (OAuth 2.0, OIDC, service accounts, Workload Identity Federation)

Nice To Haves

Direct experience building MCP servers or other AI tool/function-calling integrations
Experience with vector databases, embeddings, and retrieval-augmented generation (RAG) patterns, including Vertex AI Vector Search or AlloyDB / BigQuery vector capabilities
Background supporting business or "citizen developer" users, with the ability to translate non-technical requests into technical designs
Knowledge of data governance, PII handling, and AI safety/compliance frameworks

Responsibilities

Build and maintain Model Context Protocol (MCP) servers to securely expose internal systems, data, and tools to AI platforms.
Develop and document APIs for AI agents to interact with CRM, ERP, and other systems of record.
Design and implement the backend AI architecture on Google Cloud, utilizing services like Vertex AI, Vertex AI Agent Builder, Apigee, Cloud Run, Cloud Functions, and Workflows.
Build and optimize data pipelines to supply the data warehouse with clean, structured, AI-ready data.
Partner with business users to define agent capabilities, resolve integration challenges, and transition prototypes to production-grade workflows.
Implement authentication, authorization, logging, and observability for all integrations to monitor AI usage and data access.
Establish reusable patterns, connectors, and internal documentation to streamline future integration efforts.
Collaborate with security and compliance teams to ensure AI access to sensitive data adheres to established controls.