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: Artificial Intelligence, Generative AI, Data Engineering, AI platforms, cloud technologies, automation, MLOps, LLMOps, Python, TypeScript, Azure, Google Cloud, APIs, data integration, embeddings, vector databases
Job Description
The selected candidate will work on enterprise AI and data engineering initiatives involving multiple AI platforms and cloud technologies. The role focuses on Artificial Intelligence, Generative AI, Data Engineering, AI platforms, cloud technologies, automation, MLOps, and enterprise AI solutions. Candidates with knowledge of Python or TypeScript, Azure, Google Cloud, APIs, data integration, embeddings, vector databases, and AI platforms can apply. This position supports the design, deployment, and maintenance of enterprise AI platform solutions and involves building and maintaining enterprise connectors, plugins, and OpenAPI integrations. It provides exposure to automation and agentic AI technologies, including developing multi-agent workflows and Python-based orchestration solutions.
Roles and Responsibilities
- Platform Support: Support the design, deployment, and maintenance of enterprise AI platform solutions.
- Platform Work: Work with platforms such as Microsoft Copilot, Copilot Studio, Google Gemini Enterprise, Google Workspace, and Vertex AI.
- Integration Development: Build and maintain enterprise connectors, plugins, and OpenAPI integrations.
- System Integration: Integrate AI platforms with databases, ERP systems, and legacy applications.
- Data Grounding: Support data grounding and retrieval solutions using Microsoft Graph and Google Cloud APIs.
- RAG Pipelines: Assist in developing Retrieval-Augmented Generation (RAG) pipelines.
- Data Sources: Work with enterprise data and content sources such as SharePoint, OneDrive, and Google Drive.
- Automation Development: Support the development of multi-agent workflows.
- Frameworks: Work with frameworks such as Semantic Kernel and Azure AI Agent Service.
- Orchestration: Develop Python-based orchestration solutions where required.
- Platform Connection: Connect Power Platform, Power Automate, and Logic Apps with backend scripts.
- Business Automation: Support AI-powered business automation initiatives.
- Platform Evaluation: Evaluate new AI platforms and tools, assessing capabilities, security, performance, and integration options.
- Reporting: Prepare evaluation findings and recommendations for stakeholders.
- Governance: Implement AI governance and enterprise guardrails.
- DLP Support: Support Data Loss Prevention (DLP) policies.
- Permissions: Ensure AI outputs respect user permissions and enterprise data boundaries.
- Security: Work with Microsoft Entra ID and OAuth 2.0 concepts.
- Compliance: Support regional data residency requirements.
- Monitoring: Monitoring AI usage, API latency, response quality, and cost.
- Dashboards: Building dashboards using Power BI or Looker.
- Power Platform Administration: Supporting Power Platform governance.
- Security Management: Managing security and DLP policies.
- ALM Support: Supporting application lifecycle management (ALM).
- Compliance & Governance: Working with Microsoft Purview for compliance and governance.
- Deployment: Using GitHub and CI/CD pipelines to deploy agents and solutions.
- Environment Management: Supporting standardized environment and release management.
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.
- Experience with Microsoft Copilot Studio, Power Platform, Google Gemini Enterprise, or Vertex AI.
- 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.