Cloud Ai

About Client:

Our Client is a multinational IT services and consulting company headquartered in USA, With revenues 19.7 Billion USD, with Global work force of 3,50,000 and Listed in NASDAQ, It is one of the leading IT services firms globally, known for its work in digital transformation, technology consulting, and business process outsourcing, Business Focus on Digital Engineering, Cloud Services, AI and Data Analytics, Enterprise Applications ( SAP, Oracle, Sales Force ), IT Infrastructure, Business Process Out Source. Major delivery centers in India, including cities like Chennai, Pune, Hyderabad, and Bengaluru. Offices in over 35 countries. India is a major operational hub, with as its U.S. headquarters.

• Job Title : Cloud AI & Data Engineer
• Key Skills : GenAI, Amazon Bedrock, Azure OpenAI, or Google Vertex AI
• Job Locations : Bangalore
• Experience : 6+ Years.
• Education Qualification : Any Graduation.
• Work Mode : Hybrid.
• Employment Type : Contract.
• Notice Period : Immediate

Job Description:

Job Title:

Cloud AI & Data Engineer

Roles & Responsibilities:

· Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.G., AWS Glue, Azure Data Factory, GCP Dataflow)

· Design and implement production-ready GenAI applications using services like Amazon Bedrock, Azure OpenAI, or Google Vertex AI

· Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions

· Integrate GenAI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns

· Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and GenAI capabilities

· Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments

· Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI models

· Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies

· Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards

Project Details:

Cloud Platform managing GenAI and data services

Job Description:

We are looking for an experienced Cloud AI and Data Engineer with a strong background in cloud-native data solutions, AI/ML engineering, and emerging Generative AI (GenAI) technologies. The ideal candidate will have 6–8 years of hands-on experience in building robust data platforms, deploying scalable ML models, and integrating GenAI solutions across cloud environments.

· Design and implement production-ready GenAI applications using services like Amazon Bedrock, Azure OpenAI, or Google Vertex AI

· Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions

· Integrate GenAI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns

· Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and GenAI capabilities

· Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments

· Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI models

· Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.G., AWS Glue, Azure Data Factory, GCP Dataflow)

· Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies

· Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards

· Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.G., AWS Glue, Azure Data Factory, GCP Dataflow)

· Design and implement production-ready GenAI applications using services like Amazon Bedrock, Azure OpenAI, or Google Vertex AI

· Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions

· Integrate GenAI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns

· Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and GenAI capabilities

· Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments

· Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI models

· Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies

· Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards