AI/ML Integration Engineer ( MCP/DMCP)

Summary

SPAR Information System is seeking a hands-on AI/ML Integration Engineer to develop end-to-end AI agents and enterprise integrations. The role focuses on MCP/DMCP protocols, Snowflake-centric AI infrastructure, Slack semantic models, Salesforce data ingestion, secure integrations, RBAC, and Claude-based agent workflows.

Responsibilities

• Build production-grade **AI agents** using Claude, Snowflake data outputs, and MCP/DMCP protocol integrations
• Design agent workflows that consume Slack semantic models and Salesforce chat outputs
• Implement retrieval, context assembly, and agent orchestration pipelines
• Build and maintain **MCP protocol integrations** between Slack and Claude
• Implement **DMCP-based Snowflake Claude** integrations for agent data access
• Ensure secure, reliable, and scalable protocol communication across systems
• Ingest and model **Salesforce customer chat data** into Snowflake
• Build semantic layers, feature tables, and agent-ready datasets
• Develop ELT/ETL pipelines using Snowflake Streams, Tasks, Snowpipe, or dbt
• Build **semantic models for Slack** conversations, channels, and message metadata
• Structure Slack data for agent reasoning, retrieval, and workflow triggers
• Stand up development and production environments for agent workloads
• Implement **RBAC**, secrets management, and secure service-to-service communication
• Build monitoring, logging, and observability for all integration services

Skills

• Strong experience in **DMCP and MCP protocols**, **Snowflake**, and **Claude**

Qualifications

Must Haves

• strong experience in **DMCP and MCP protocols**, **Snowflake**, and **Claude**

Benefits

• Remote work arrangement
• 3–6 months contract-to-hire or long-term contract