Carrier Recruitment 2026 | Associate AI & Data Engineering | Freshers

Job Overview

Role: Associate, AI & Data Engineering Location: Bangalore Experience: 0–2 years Qualification: Bachelor’s Degree in Computer Science, Data Science, Information Systems, Engineering, or a related field Key Skills: Python, TypeScript, JavaScript, Generative AI, Large Language Models (LLMs), APIs, data integration, Retrieval-Augmented Generation (RAG), Prompts, prompt engineering, Embeddings, Vector databases, AI model lifecycle, Data processing, ingestion, Microsoft Azure, Azure AI Foundry, Azure AI Services, Google Cloud Platform, Vertex AI, Microsoft 365, Microsoft Power Platform, access control, data privacy, data security, compliance, responsible AI, multi-agent workflows, Semantic Kernel, Azure AI Agent Service, Power Platform, Power Automate, Logic Apps, MLOps, LLMOps, Azure Monitor, Application Insights, GitHub CI/CD, Microsoft Purview

Job Description

Carrier is hiring for the position of Associate, AI & Data Engineering in Bangalore. This role focuses on Artificial Intelligence, Generative AI, Data Engineering, AI platforms, cloud technologies, automation, MLOps, and enterprise AI solutions. Candidates with a Bachelor’s degree and 0–2 years of relevant experience can apply. The role involves supporting the design, deployment, and maintenance of enterprise AI platform solutions, building connectors and integrations, assisting with data grounding, and developing RAG pipelines. It also provides exposure to automation, agentic AI technologies, and evaluating emerging AI platforms, while ensuring governance, security, and performance of AI solutions.

Roles and Responsibilities

• Enterprise AI Platform Solutions: Support the design, deployment, and maintenance of enterprise AI platform solutions.
• Platform Integration: Work with platforms such as Microsoft Copilot, Copilot Studio, Google Gemini Enterprise, Google Workspace, and Vertex AI. Build and maintain enterprise connectors, plugins, and OpenAPI integrations. Integrate AI platforms with databases, ERP systems, and legacy applications.
• Data Grounding & Retrieval: Support data grounding and retrieval solutions using Microsoft Graph and Google Cloud APIs. Assist in developing Retrieval-Augmented Generation (RAG) pipelines. Work with enterprise data and content sources such as SharePoint, OneDrive, and Google Drive.
• Automation & Agentic AI: Support the development of multi-agent workflows. Work with frameworks such as Semantic Kernel and Azure AI Agent Service. Develop Python-based orchestration solutions where required. Connect Power Platform, Power Automate, and Logic Apps with backend scripts. Support AI-powered business automation initiatives.
• AI Platform Evaluation: Participate in evaluating emerging AI platforms and technologies, assessing capabilities, security, performance, and integration options, and preparing evaluation findings and recommendations for stakeholders.
• Governance, Security & Performance: Implement AI governance and enterprise guardrails. Support Data Loss Prevention (DLP) policies. Ensure AI outputs respect user permissions and enterprise data boundaries. Work with Microsoft Entra ID and OAuth 2.0 concepts. Support regional data residency requirements. Monitor AI usage, API latency, response quality, and cost. Build dashboards using Power BI or Looker.
• Power Platform Administration: Support Power Platform governance, managing security and DLP policies. Support application lifecycle management (ALM). Work with Microsoft Purview for compliance and governance. Use GitHub and CI/CD pipelines to deploy agents and solutions. Support standardized environment and release management.
• MLOps & LLMOps: Gain exposure to operationalizing machine learning and Generative AI solutions, utilizing technologies like Azure AI Foundry, Azure Monitor, Application Insights, GitHub CI/CD pipelines, model lifecycle management, prompt lifecycle management, AI observability, and Responsible AI practices.

Skills and Eligibility Criteria

Educational Background: 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.

Mandatory Technical Skills:

• Basic hands-on experience with Python, TypeScript, JavaScript, or a similar programming language
• Ability to build scripts, integrations, custom plugins, and applications using programming languages
• Basic understanding of Generative AI, Large Language Models (LLMs), APIs and data integration, Retrieval-Augmented Generation (RAG), Prompts and prompt engineering, Embeddings, Vector databases, AI model lifecycle concepts, Data processing and ingestion
• Familiarity with Microsoft Azure, Azure AI Foundry, Azure AI Services, Google Cloud Platform, Vertex AI, Microsoft 365, Microsoft Power Platform
• Awareness of access control, data privacy, data security, compliance, Responsible AI principles
• 0–2 years of hands-on experience with Microsoft Copilot Studio, Power Platform, Google Gemini Enterprise, or Vertex AI
• Strong proficiency in Python or TypeScript for integrations, data ingestion scripts, and LLM API integrations
• Understanding of Azure AI Foundry, Azure AI Services, and Google Cloud Platform
• Experience or knowledge of graph data, embeddings, vector databases, and enterprise content management systems
• Experience with continuous integration and deployment pipelines for AI agents, prompt configurations, and platform automation

Competencies:

• Good communication and documentation skills
• Ability to learn quickly and take ownership of assigned tasks