Senior AI Cloud Engineer (AWS Bedrock & Generative AI)

Zorba AI; Maharashtra; On-site; INR 350,000 - 550,000; Full time

Job summary

Zorba AI in Maharashtra, India, is seeking a Senior AI Cloud Engineer with 12+ years of experience in Cloud Engineering, DevOps, Data Engineering, or AI infrastructure. The role focuses on building GenAI infrastructure on AWS, including Bedrock, cost optimization, observability, and scalable cloud services.

The candidate will design, deploy, and monitor GenAI workloads, develop Python automation, and collaborate with cross-functional teams to ensure reliable, production-grade solutions.

Qualifications

• 12+ years of experience in Cloud Engineering, DevOps, Data Engineering, or AI infrastructure.
• Hands-on experience with AWS and Amazon Bedrock is mandatory.
• Experience with AWS monitoring services and GenAI cost optimizations.
• Strong Python programming skills and knowledge of LLM observability.
• Ability to design scalable GenAI infrastructure on AWS.

Responsibilities

• Design, develop, and deploy AI agents using AWS Agents for Amazon Bedrock.
• Build scalable GenAI infrastructure and supporting cloud services on AWS.
• Develop observability and data-log pipelines for GenAI workloads.
• Implement monitoring and alerting with CloudWatch, EventBridge, SNS, and Lambda.
• Monitor Bedrock usage, token consumption, and cost metrics.
• Implement GenAI cost optimization and FinOps strategies.
• Develop production-grade Python scripts for data processing and AI workflows.
• Design dashboards for LLm performance, usage, and health.
• Evaluate AWS services for monitoring and automation needs.
• Troubleshoot production issues across AI, cloud, and observability layers.
• Collaborate with architecture, DevOps, data, and application teams.

Skills

AWS

Amazon Bedrock

Python

LLM observability

FinOps

Cloud monitoring

AWS CloudWatch

AWS Lambda

Amazon EventBridge

Amazon SNS

Job description

Role Overview

We are looking for a highly experienced Senior AI Cloud Engineer with 12+ years of experience in Cloud Engineering, DevOps, Data Engineering, or AI Infrastructure, with strong hands-on expertise in AWS and Generative AI.

The role will focus on building and optimizing GenAI infrastructure, AWS Bedrock agents, observability pipelines, LLM usage monitoring, and cloud cost optimization. The ideal candidate should be hands-on with Amazon Bedrock, Python, AWS monitoring services, LLM observability, and FinOps.

AWS Bedrock Experience Is Mandatory.

Key Responsibilities

• Design, develop, and deploy AI agents using AWS Agents for Amazon Bedrock.
• Build scalable GenAI infrastructure and supporting cloud services on AWS.
• Develop end-to-end observability and data-log pipelines for GenAI workloads.
• Implement monitoring and alerting using CloudWatch, EventBridge, SNS, Lambda, and related AWS services.
• Analyze application and MuleSoft logs to identify failures, anomalies, and integration issues.
• Monitor Amazon Bedrock usage, token consumption, model utilization, and billing metrics.
• Implement GenAI cost optimization and FinOps strategies to control LLM/AWS expenditure.
• Develop production-grade Python scripts and automation for data processing, API integration, AI workflows, and cloud operations.
• Design dashboards and reporting mechanisms for LLM performance, usage, cost, and operational health.
• Evaluate and select appropriate AWS services for different monitoring, alerting, and automation requirements.
• Troubleshoot production issues across AI, cloud, integration, and observability layers.
• Work with architecture, DevOps, data, and application teams to establish scalable and reliable GenAI solutions.

Mandatory Skills

• 12+ years of overall experience in Cloud Engineering, DevOps, Data Engineering, AI Engineering, or related technologies.
• Strong hands-on experience with AWS.
• Mandatory hands-on experience with Amazon Bedrock.
• Experience with AWS Agents for Amazon Bedrock / Agent-based GenAI solutions.
• Strong Python programming experience.
• Experience with LLM observability and monitoring.
• Strong knowledge of:
• AWS CloudWatch
• AWS Lambda
• Amazon SNS
• Amazon EventBridge
• AWS logging and monitoring
• Understanding of LLM tokenization, prompt engineering, model usage, and pricing/cost structures.
• Experience monitoring and optimizing GenAI/AWS costs.

Skills: cloud,aws,devops,python,bedrock