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Senior AI Cloud Engineer – AWS & Generative AI
Zorba Consulting India · India
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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