AI Platform Integration Engineer

Job not on LinkedIn

🔥 7 minutes ago

🇺🇸 United States – Remote

💵 $100k - $120k / year

⏱ Part Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 1%

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VPS

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1922

📚 Education

🏛️ Government

🔒 Cybersecurity

Education • Government • Cybersecurity

VPS is your trusted source for managed learning solutions, serving commercial, government, and military clients globally. With a focus on collaboration and leveraging learning technology, VPS delivers tailored curriculum development, training strategies, and efficient learning administration services. Their innovative approach ensures that organizations can enhance performance, upskill their workforce, and effectively navigate the complexities of modern training environments.

📋 Description

• Support integration of enterprise platform services with an existing AI Gateway • Collaborate with AI Gateway engineering teams to establish and maintain secure integration interfaces • Configure and support AI service connectivity, including model routing and API-based integrations • Troubleshoot technical issues involving AI gateway connectivity, service access, and platform integrations • Coordinate technical requirements, integration schedules, dependencies, and issue resolution across engineering teams • Deploy, host, configure, and operate Model Context Protocol (MCP) servers within the enterprise platform • Support standardized interfaces that allow AI applications and agents to discover and access approved tools and services • Integrate MCP servers with existing APIs and enterprise data services • Monitor MCP server availability, connectivity, and operational performance • Support secure access to tools and services exposed through MCP interfaces • Integrate usage tracking and cost metering for AI and Large Language Model (LLM) traffic • Support monitoring of token consumption, API usage, and associated AI service costs • Configure or integrate reporting capabilities for consumption visibility and internal cost allocation • Collaborate with platform teams to establish appropriate usage limits and monitoring practices • Configure and support rate limiting, quotas, and usage restrictions for AI endpoints • Integrate content-control and AI guardrail services into gateway request and response workflows • Support implementation of security and usage policies for AI-enabled applications • Assist with integration of AWS AI services, including Amazon Bedrock and related capabilities • Troubleshoot API connectivity, authorization, and configuration issues • Serve as a technical liaison between the enterprise platform engineering team and the AI Gateway engineering team • Provide technical updates to engineering teams and project stakeholders • Document AI service integrations, MCP server configurations, operational procedures, and troubleshooting processes • Support initial Minimum Viable Product (MVP) delivery and identify opportunities for future platform enhancements

🎯 Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline, or equivalent professional experience • Minimum of 3 years of hands-on professional experience in software engineering, cloud engineering, or platform engineering • Working knowledge of AI/LLM gateway concepts, including model routing, token-based usage tracking, rate limiting, and content guardrails • Hands-on experience deploying or hosting MCP servers, or comparable integrations that expose tools and APIs to AI applications or agents • Hands-on experience with AWS cloud services, including Amazon Bedrock or Amazon SageMaker • Experience working with API gateways and REST APIs • Understanding of cloud-based application integration, service connectivity, and API security • Strong troubleshooting and technical problem-solving skills • Excellent written and verbal communication skills, with the ability to coordinate effectively across multiple technical teams • Ability to work independently and manage technical deliverables in a part-time capacity • Candidates must be able to work independently, communicate effectively, and collaborate successfully with team members in a virtual work environment • New hires assigned on this project will be required to undergo and pass drug tests per our client's contract requirements • Requires U.S. citizenship status • Preferred: Experience developing, extending, or customizing Model Context Protocol (MCP) servers • Preferred: Experience with LLM gateway or proxy technologies such as LiteLLM, Kong AI Gateway, or comparable platforms • Preferred: Experience implementing AI usage metering, token consumption tracking, chargeback reporting, or FinOps capabilities • Preferred: Experience with Amazon Bedrock Guardrails or comparable AI content-control services • Preferred: Experience configuring AI gateway rate limiting, quotas, and usage policies • Preferred: Familiarity with AI agent architectures and tool integration patterns • Preferred: Experience integrating AI services with enterprise applications and data platforms • Preferred: Experience supporting cloud-native platforms in large enterprise or regulated environments • Preferred: Familiarity with security, access management, and governance considerations for enterprise AI integrations

🏖️ Benefits

• Part-time schedule of approximately 20 hours per week • Fully remote work arrangement

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