Senior AI Cloud Engineer - AWS/Generative AI in Pune, भारत

Role Overview : We are seeking a highly technical Cloud Engineer to build and optimize our Generative AI https://jobeax.com/link/VVhabah3jNnBUVdl role focuses on deploying AWS Bedrock agents, automating workflows with Python, and creating robust observability and billing pipelines for LLM https://jobeax.com/link/EyRoMFFzs0UZEYMq will be responsible for ensuring that our AI services are not only functional but also cost-effective and highly monitored through advanced logging and https://jobeax.com/link/EF8JPf7aDthzqnSA Responsibilities : - AI Agent Orchestration : Design and deploy specialized agents using AWS Agents for Amazon Bedrock to automate complex multi-step business processes.- Observability & Alerting : Build end-to-end "Data Log" pipelines.- Identify and implement the correct AWS services for alerting (e.g., CloudWatch, SNS, or Lambda) based on log anomalies.- Integration & Middleware : Manage and analyze Mulesoft logs to ensure seamless connectivity between legacy systems and modern AI services.- Financial Operations (FinOps) : Monitor billing metrics for LLM usage and AWS Bedrock services to prevent cost overruns and optimize token consumption.- Python Automation : Write production-grade Python scripts for data processing, agent logic, and infrastructure https://jobeax.com/link/6S9Yk4PtCFirCoFU Requirements : - Core AWS AI Services : Hands-on experience with AWS Bedrock and AWS Agent Core logic.- Programming : High proficiency in Python (specifically for data manipulation and API integrations).- Logging & Monitoring : Deep understanding of log aggregation.- Experience with Mulesoft logs is a significant plus.- Alerting Frameworks : Ability to determine which AWS service to use for specific alerts (CloudWatch Alarms vs. EventBridge vs. Managed Grafana).- LLM Knowledge : Understanding of how LLMs work, including tokenization, prompt engineering, and the cost structure of different models. (ref:hirist.tech)