About the Job
Carrier is hiring for the Associate, AI & Data Engineering role for candidates interested in enterprise AI, data engineering, cloud platforms and automation. The role focuses on building and managing AI capabilities that can be used securely across an organisation.
In this role, you will work with platforms like Microsoft Copilot, Copilot Studio, Google Gemini Enterprise and Vertex AI. The work includes building enterprise connectors, AI integrations, Retrieval-Augmented Generation pipelines and automated workflows.
The role also covers AI governance, security, access control, monitoring and cost optimisation. You may work with Microsoft Power Platform, Azure AI, Google Cloud, GitHub and CI/CD pipelines while helping deploy AI solutions into production.
This is a good opportunity for early-career candidates who have a strong interest in AI, Python or TypeScript, cloud platforms, data integration and enterprise automation and want to work on practical AI solutions.
Job Overview
Eligibility Criteria
- Candidates should have a Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering or a related field.
- Candidates with 0–2 years of relevant experience in AI platforms, cloud engineering, automation, data platforms or enterprise application development can apply.
- Should have basic hands-on programming experience with Python, TypeScript, JavaScript or a similar programming language.
- Should have familiarity with Microsoft Azure, Google Cloud Platform, Microsoft 365, Power Platform or similar enterprise platforms.
- Should have a basic understanding of generative AI concepts, APIs, data integration, retrieval, prompts, embeddings or model lifecycle concepts.
- For the technical qualification, hands-on experience with enterprise AI tools such as Microsoft Copilot Studio, Power Platform, Google Gemini Enterprise and Vertex AI is mentioned.
- Should understand basic security concepts including access control, data privacy, compliance and responsible AI.
- Should be comfortable learning quickly, documenting solutions and working with cross-functional teams.
- Should be able to take ownership of assigned tasks and communicate technical work clearly.
Key Responsibilities
- Design, deploy and maintain solution architecture across Microsoft Copilot, Copilot Studio, Google Gemini Enterprise, Google Workspace and Vertex AI.
- Build enterprise connectors, plugins and OpenAPI manifests to connect AI platforms with databases, ERP systems and legacy applications.
- Design and improve Retrieval-Augmented Generation (RAG) pipelines using Microsoft Graph and Google Cloud APIs.
- Develop multi-agent workflows using tools such as Semantic Kernel, Azure AI Agent Service or custom Python-based orchestration.
- Connect Power Platform, Power Automate and Logic Apps with backend scripts using Python or TypeScript.
- Evaluate emerging AI platforms and tools and compare them against enterprise requirements.
- Prepare recommendation reports for leadership and other stakeholders based on AI platform evaluations.
- Help implement AI governance, tenant isolation and Data Loss Prevention policies.
- Ensure AI solutions follow access controls, user permissions, Microsoft Entra ID, OAuth 2.0 and regional data residency requirements.
- Monitor AI usage, API latency, response quality and cost trends.
- Build monitoring and reporting dashboards using Power BI or Looker.
- Govern Microsoft Power Platform and Microsoft 365 environments, including security, DLP, ALM and compliance.
- Use GitHub and CI/CD pipelines to deploy AI agents and solutions into production.
- Operationalise machine learning and generative AI solutions across the Azure AI ecosystem.
- Work with Azure AI Foundry, Azure Monitor and Application Insights for AI operations and observability.
- Support model and prompt lifecycle management, monitoring and responsible AI practices.
Skills Required
- Python / TypeScript: Ability to build custom plugins, integrations, data ingestion scripts and backend automation.
- Generative AI: Basic understanding of LLMs, prompts, embeddings, retrieval and AI-assisted workflows.
- AI Platforms: Exposure to Microsoft Copilot Studio, Power Platform, Google Gemini Enterprise and Vertex AI.
- Cloud: Understanding of Microsoft Azure, Azure AI Foundry, Azure AI Services and Google Cloud Platform.
- RAG: Understanding of Retrieval-Augmented Generation pipelines and enterprise data grounding.
- APIs & Data Integration: Knowledge of APIs, data ingestion, enterprise connectors and integration with business systems.
- Vector Databases: Familiarity with embeddings, vector databases and graph data.
- DevOps & CI/CD: Understanding of GitHub and continuous integration and deployment pipelines.
- Power Platform: Knowledge of Power Automate, Logic Apps and Power Platform administration.
- Security: Awareness of access control, data privacy, compliance, DLP and responsible AI practices.
- Monitoring: Familiarity with Azure Monitor, Application Insights and AI performance monitoring.
- Communication: Ability to document technical solutions clearly and work with cross-functional teams.
Skills to Add in Your Resume
TECHNICAL SKILLS
| Programming | Python, TypeScript, JavaScript |
| Generative AI | LLMs, Prompt Engineering, RAG, AI Agents, Embeddings |
| AI Platforms | Microsoft Copilot Studio, Google Gemini Enterprise, Vertex AI, Azure AI |
| Cloud | Microsoft Azure, Google Cloud Platform, Azure AI Foundry, Azure AI Services |
| Data | Data Integration, Data Ingestion, Graph Data, Vector Databases |
| Automation | Power Automate, Logic Apps, Power Platform, AI Workflow Automation |
| DevOps | GitHub, CI/CD, Release Automation |
| Monitoring | Azure Monitor, Application Insights, Power BI, Looker |
| Security | Access Control, OAuth 2.0, Data Loss Prevention, Data Privacy, Responsible AI |
Resume Tip: This role has a wide technical stack, but don't simply copy all the tools into your resume. Add the technologies you have actually used in projects, internships or coursework. For a fresher, a good AI project using Python, APIs, RAG, embeddings or an AI agent can be more useful than just listing many tools.
Benefits
- Carrier offers a competitive total rewards package for eligible employees.
- Benefits and wellbeing programs are designed to support employees' health, security and overall success.
- The exact benefits can vary depending on the role and location.
- The role gives exposure to enterprise AI, data engineering, cloud platforms and automation.
- Employees can get experience working with modern AI platforms such as Microsoft Copilot and Google Gemini Enterprise.
- The role also provides exposure to AI governance, security, data integration and responsible AI practices.
- Working with cross-functional teams can provide experience in enterprise technology and AI projects.
Who Can Apply?
- Candidates with a Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering or a related field can apply.
- Candidates with 0–2 years of relevant experience in AI platforms, cloud engineering, automation, data platforms or enterprise application development can consider this role.
- Fresh graduates with practical exposure to Python, TypeScript, JavaScript or similar programming languages can consider applying.
- Candidates familiar with Microsoft Azure, Google Cloud Platform, Microsoft 365 or Power Platform can be a good fit.
- Those who understand basic generative AI concepts such as LLMs, prompts, embeddings, APIs and RAG can apply.
- Candidates who have worked on AI projects, automation tools, data pipelines or AI agents can highlight those projects in their resume.
- Applicants should have awareness of data privacy, access control, compliance and responsible AI.
- Candidates who can learn quickly, document their work and collaborate with different teams are also suitable.
How to Apply
01
Check Your Eligibility
Check the education and experience requirements before applying. The role requires a bachelor's degree in a relevant field and mentions 0–2 years of relevant experience.
02
Prepare Your Resume
Highlight your actual experience with Python, TypeScript, AI, cloud platforms, APIs, RAG, data integration or automation. If you are a fresher, mention relevant projects clearly.
03
Visit the Carrier Careers Page
Search for Job ID 30213204 and open the Associate, AI & Data Engineering position to review the latest application details.
04
Submit Your Application
Complete the required details and submit your application through the official Carrier careers portal. Make sure your resume reflects the skills relevant to the role.
Application Tip
For this role, projects can make a big difference, especially for early-career candidates. If you have built an AI chatbot, RAG application, AI agent, automation workflow or data pipeline, explain what you built and which technologies you used.