Senior AI Cloud Engineer – AWS & Generative AI

Zorba Consulting Limited

Pune District

On-site

INR 3,500,000 - 5,500,000

Full time

7 days ago

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Job summary

Zorba Consulting Limited is seeking a Senior AI Cloud Engineer in Pune to design, deploy, and optimize AI infrastructure on AWS Bedrock. You'll build agent orchestration, automate data workflows, and implement robust observability for large language models.

The role emphasizes cost-aware AI deployments and scalable GenAI solutions. You will collaborate with engineering and business teams to deliver reliable GenAI capabilities, monitor usage and billing, and fine-tune model performance across

Qualifications

AWS Bedrock and Agent Core concepts knowledge
Strong Python programming and automation skills
Experience with Generative AI and LLMs
Strong knowledge of AWS Cloud services
Experience with CloudWatch, Lambda, SNS, EventBridge and alerting mechanisms
Strong understanding of logging, monitoring, and observability
Knowledge of LLM tokenization, prompt engineering, model usage, and cost optimization
Experience with API integrations and data processing
Strong troubleshooting and production support experience

Responsibilities

Design and deploy AI agents using AWS Bedrock for complex workflows.
Develop and maintain Python automation for data processing and cloud operations.
Build end-to-end logging, monitoring, and observability pipelines for AI workloads.
Analyze MuleSoft logs and integrate with AWS monitoring and alerting solutions.
Implement alerts using CloudWatch, SNS, Lambda, EventBridge, and other AWS services.
Monitor AWS Bedrock and LLM usage, billing, token consumption, and cost metrics.
Identify opportunities to optimize LLM usage and reduce unnecessary cloud/AI costs.
Work with different LLM models and understand their tokenization, pricing, context limits, and performance characteristics.
Develop production-grade solutions for Generative AI and cloud infrastructure.
Troubleshoot production issues across AI agents, APIs, logs, integrations, and AWS services.
Collaborate with engineering and business teams to deliver reliable and scalable GenAI solutions.

Skills

AWS Bedrock

Python

Generative AI

LLMs

AWS Cloud

Observability

Cost optimization

API integration

Education

Bachelor's degree in CS/IT/Engineering

Job description

Job Summary

We are looking for a highly skilled Senior AI Cloud Engineer with strong expertise in AWS, Amazon Bedrock, Python, and Generative AI. The role will focus on designing, deploying, monitoring, and optimizing AI infrastructure and AWS Bedrock Agents. The ideal candidate should have strong experience in AI agent orchestration, observability, automation, LLM cost monitoring, and AWS cloud services.

Responsibilities

Design and deploy AI agents using AWS Agents for Amazon Bedrock for complex business workflows.
Develop and maintain Python-based automation for data processing, API integrations, agent workflows, and cloud operations.
Build end-to-end logging, monitoring, and observability pipelines for AI/LLM workloads.
Analyze application and MuleSoft logs and integrate them with AWS monitoring and alerting solutions.
Implement alerts using Amazon CloudWatch, SNS, Lambda, EventBridge, and other AWS services based on operational requirements.
Monitor AWS Bedrock and LLM usage, billing, token consumption, and cost metrics.
Identify opportunities to optimize LLM usage and reduce unnecessary cloud/AI costs.
Work with different LLM models and understand their tokenization, pricing, context limits, and performance characteristics.
Develop production-grade solutions for Generative AI and cloud infrastructure.
Troubleshoot production issues across AI agents, APIs, logs, integrations, and AWS services.
Collaborate with engineering and business teams to deliver reliable and scalable GenAI solutions.

Must-Have Skills

AWS Bedrock - Mandatory
Hands-on experience with AWS Bedrock Agents / Agent Core concepts
Strong Python programming and automation skills
Experience with Generative AI / LLMs
Strong knowledge of AWS Cloud services
Experience with CloudWatch, Lambda, SNS, EventBridge and alerting mechanisms
Strong understanding of logging, monitoring, and observability
Knowledge of LLM tokenization, prompt engineering, model usage, and cost optimization
Experience with API integrations and data processing
Strong troubleshooting and production support experience

Good-to-Have Skills