Opportunity brief
Carrier is hiring for the role of Associate, AI & Data Engineering!
Responsibilities of the Candidate:
- Design, deploy, and maintain solution architectures across Microsoft Copilot, Copilot Studio, Google Gemini Enterprise, Google Workspace, and Vertex AI. - Build and maintain enterprise connectors, plugins, and OpenAPI manifests to integrate AI platforms with proprietary - y databases, ERP systems, and legacy applications. - Design, optimize, and scale Retrieval-Augmented Generation (RAG) pipelines using Microsoft Graph and Google Cloud APIs to deliver accurate and context-aware AI interactions. - Design and implement autonomous multi-agent workflows using Semantic Kernel, Azure AI Agent Service, or custom Python-based orchestration frameworks. - Integrate low-code automation platforms such as Power Platform, Power Automate, and Logic Apps with programmatic backend solutions using Python or TypeScript. - Evaluate emerging AI platforms and tools such as Codex, Claude, and Kong AI against enterprise requirements. - Conduct structured AI platform assessments and prepare recommendation reports for leadership and stakeholders. - Implement and enforce enterprise AI governance, tenant isolation, and Data Loss Prevention (DLP) policies across Microsoft Purview and Google Workspace. - Manage AI access controls to ensure outputs comply with enterprise data boundaries, user permissions, Microsoft Entra ID, OAuth 2.0, and regional data residency requirements. - Monitor and optimize AI usage, API latency, response quality, licensing, and cost trends. - Develop Power BI and Looker dashboards to provide visibility into AI performance, usage, and total cost of ownership. - Govern Microsoft Power Platform and Microsoft 365 environments, including security, DLP, Application Lifecycle Management (ALM), and compliance. - Manage standardized environment and release processes to enable scalable, secure, and well-governed automation. - Use GitHub and CI/CD pipelines to deploy AI agents, applications, and Power Platform solutions to production environments. - Operationalize machine learning and generative AI solutions across the Azure AI ecosystem, including Azure AI Foundry, Azure Monitor, and Application Insights. - Implement CI/CD-driven deployments using GitHub to support reliable and repeatable AI solution delivery. - Manage model and prompt lifecycle processes across AI and LLM solutions. - Implement observability, monitoring, performance optimization, and cost controls for AI workloads. - Apply responsible AI, security, compliance, and governance practices throughout the AI/ML lifecycle.
Requirements:
- Education: Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.
- Experience: 0-2 years of relevant experience in AI platforms, cloud engineering, automation, data platforms, or enterprise application development.
- Programming foundation: Basic hands-on experience with Python, TypeScript, JavaScript, or a similar programming language.
- Cloud and platform understanding: Familiarity with Microsoft Azure, Google Cloud Platform, Microsoft 365, Power Platform, or comparable enterprise platforms.
- AI and data fundamentals: Basic understanding of generative AI concepts, APIs, data integration, retrieval, prompts, embeddings, or model lifecycle concepts.
- Security mindset: Awareness of access control, data privacy, compliance, and responsible AI principles in enterprise environments.
- Communication and ownership: Ability to learn quickly, document solutions clearly, collaborate with cross-functional teams, and take ownership of assigned tasks.