AI Platform Engineer

Job not on LinkedIn

🕒 March 11

🇺🇸 United States – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

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KANINI

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2003

🤝 B2B

🏢 Enterprise

🤖 Artificial Intelligence

B2B • Enterprise • Artificial Intelligence

KANINI is a global digital engineering and IT services firm that helps enterprises transform through product engineering, cloud enablement, data analytics & AI, intelligent automation, and ServiceNow solutions. It builds cloud-native applications, modernizes legacy systems, implements AI/ML and data platforms, and delivers managed outcomes via flexible engagement models for clients across healthcare, banking, energy, government and technology sectors.

📋 Description

• AI Enablement in Azure & Snowflake Design, deploy, and maintain MCP servers in Azure and Snowflake-based environments to support AI agents and developer workflows. • Integrate AI capabilities with existing data pipelines, data warehouses, and lakehouse architectures in Azure and Snowflake. • Collaborate with data engineering teams to ensure data quality, lineage, and observability for AI use cases. • Establish secure connectivity between AI clients, AI agents, and backend data/services. • Define and implement APIs, connectors, and integration patterns between AI agents and enterprise systems. • Troubleshoot and optimize connectivity issues between AI clients/agents and Azure, Snowflake, and other downstream systems. • Establish guardrails for AI usage, including data classification, allowed data domains, and acceptable use of AI within the environment. • Document and enforce standards, patterns, and reusable components for AI integrations across teams.

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience. • Solid hands-on experience with Microsoft Azure (e.g., Azure Data services, networking, security, identity). • Practical experience with Snowflake (data modeling, security, roles, governance, integrations). • Proven experience enabling or integrating AI/ML systems with enterprise data platforms (e.g., LLMs, AI agents, or similar architectures). • Strong understanding of access control, security, and governance concepts (RBAC, ABAC, encryption, key management, data privacy). • Experience implementing APIs, microservices, or integration frameworks to connect applications and services. • Familiarity with infrastructure-as-code (e.g., Terraform, Bicep, ARM templates) and DevOps/CI-CD practices.

🏖️ Benefits

• Remote work