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Zorba Consulting India

Senior AI Cloud Engineer – AWS & Generative AI

India

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hirly's read of this role

Role family
Engineering
Seniority
Senior
Country
IN
Work mode
On-site / unstated
First seen by hirly
26 Sept 2026

Derived automatically from the posting. Sign up to see how the role scores against your own resume.

the posting

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.

Key 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

MuleSoft / MuleSoft log analysis

Amazon Managed Grafana

AWS Cost Explorer / AWS Billing and FinOps

Experience building AI/LLM usage dashboards

Experience with Bedrock Knowledge Bases and RAG

Experience with REST APIs and middleware integrations

Infrastructure automation / IaC

Original posting on Zorba Consulting India's site ↗

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