Associate – AI & Data Engineering

Candidates typically face a three‑stage process: an initial timed aptitude and coding test, followed by a technical interview that probes AI platform knowledge, programming proficiency, and cloud fundamentals, and finally an HR round assessing cultural fit and communication. The difficulty is moderate, with emphasis on practical problem‑solving and clear articulation of concepts. Preparing with real‑world project examples and reviewing AI service documentation helps significantly.

Carrier promotes a balanced work‑life environment with flexible timings and a focus on employee well‑being. The company encourages continuous learning through internal workshops, certifications, and cross‑functional projects, enabling rapid skill growth. Employees often cite supportive leadership, clear career paths, and a collaborative culture as key strengths.

• Minimum: Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or related field. • Preferred branches: Computer Science, Information Technology, Electronics & Communication, Electrical Engineering, or similar. • Academic performance: Typically 60% or higher in aggregate (or CGPA 6.0/10). • Batch: Graduates of 2023, 2024, or 2025 are eligible. • Backlog policy: No active backlogs at the time of application; up to two backlogs cleared before joining are acceptable. • Experience: 0–2 years of relevant exposure to AI platforms, cloud services, or data engineering. • Additional: Good communication skills, willingness to learn, and ability to work in a collaborative team environment.

Round 1: Online Aptitude & Coding Assessment → Round 2: Technical Interview (AI platform concepts, programming, cloud fundamentals) → Round 3: HR Interview (fit, communication, motivation)

Carrier Global Corporation, a leader in intelligent climate and energy solutions, is expanding its Digital Technology division to build next‑generation enterprise AI capabilities. With a legacy of innovation in temperature control, air quality, and sustainable transportation, Carrier now focuses on integrating AI, cloud, and data engineering to drive smarter, more efficient operations for its global customers. The company’s culture blends engineering rigor with a commitment to sustainability, offering fresh graduates a platform to work on cutting‑edge technologies while contributing to real‑world impact. The role of Associate – AI & Data Engineering is designed for recent graduates or candidates with up to two years of experience who are eager to dive into the world of Generative AI, MLOps, and cloud‑native data pipelines. As an associate, you will collaborate with senior AI platform engineers, data scientists, and product teams to design, deploy, and maintain AI solutions that power internal tools and customer‑facing services. You will gain hands‑on exposure to Microsoft Copilot Studio, Google Gemini Enterprise, Azure AI Foundry, and Vertex AI, learning how to integrate large language models (LLMs) with enterprise data sources such as SharePoint, OneDrive, and Google Drive. Key responsibilities include: 1. Supporting the design, deployment, and upkeep of enterprise AI platform solutions across Azure and Google Cloud. 2. Building and maintaining connectors, plugins, and OpenAPI integrations for AI services. 3. Integrating AI platforms with ERP systems, databases, and legacy applications. 4. Developing Retrieval‑Augmented Generation (RAG) pipelines and managing data grounding using Microsoft Graph and Google Cloud APIs. 5. Assisting in the creation of multi‑agent workflows using Semantic Kernel and Azure AI Agent Service. 6. Writing Python‑based orchestration scripts and linking Power Platform components (Power Automate, Logic Apps) with backend services. 7. Evaluating emerging AI tools such as Codex, Claude, and Kong AI against enterprise requirements. 8. Implementing AI governance, data loss prevention policies, and ensuring compliance with regional data residency rules. 9. Monitoring AI usage, latency, cost, and quality, and building operational dashboards with Power BI or Looker. 10. Supporting CI/CD pipelines, GitHub workflows, and ALM processes for AI agents and prompt configurations. The tech stack revolves around Python, TypeScript/JavaScript, Azure AI services (Copilot, AI Foundry), Google Cloud services (Vertex AI, Gemini Enterprise), vector databases, embeddings, and DevOps tools like GitHub, CI/CD, Azure Monitor, and Application Insights. Over time, associates can progress to roles such as AI Engineer, Generative AI Engineer, MLOps Engineer, or Cloud Engineer, with clear pathways to senior technical leadership or product ownership. Why join Carrier? The company offers a vibrant environment where fresh talent works alongside industry veterans on mission‑critical AI projects. Employees benefit from structured learning programs, mentorship, and exposure to both Microsoft and Google ecosystems, positioning them for rapid career growth in the booming AI and data engineering market.