Senior AI Cloud Engineer

Saxon Global; Maharashtra; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Saxon Global in Pune, India, seeks a Senior AI DevOps or Cloud Data Engineer to build and optimize GenAI infrastructure within AWS Bedrock. The role focuses on deploying Bedrock agents, automating workflows with Python, and creating robust observability and billing pipelines for LLM usage.

You will ensure cost-efficient AI services, monitor with logging and alerts, and work onsite four days a week. Ideal candidates have Bedrock and AWS Agent Core experience and strong Python skills, with a

Qualifications

• Hands-on experience with AWS Bedrock and AWS Agent Core logic.
• Proficiency in Python for data manipulation and API integrations.
• Logging & Monitoring with log aggregation; Mulesoft logs a plus.
• Alerting frameworks: choose CloudWatch, EventBridge, or Grafana for alerts.
• LLM knowledge including tokenization, prompts, and cost structures.

Responsibilities

• AI Agent Orchestration: design/deploy agents with AWS Bedrock Agent Core.
• Observability & alerting: build data log pipelines and alerting using AWS services.
• Integration & middleware: analyze Mulesoft logs for connectivity.
• FinOps: monitor billing metrics for LLM usage and Bedrock services.
• Python automation: develop production-grade scripts for data processing and infra tasks.

Skills

Python

AWS Bedrock

AWS Agent Core

Mulesoft logs

CloudWatch

SNS

Lambda

EventBridge

Grafana

LLM knowledge

FinOps

Tools

AWS Bedrock

AWS Agent Core

Mulesoft

CloudWatch

EventBridge

Grafana

Job description

Looking for Senior AI DevOps or Cloud Data Engineer focused on Generative AI (GenAI) observability and cost optimization within the AWS ecosystem.

Bedrock experience a must.

Location : Pune, India (Onsite requirement: 4 days/week)

Job Description:

Role Overview

• We are seeking a highly technical Cloud Engineer to build and optimize our Generative AI infrastructure.
• This role focuses on deploying AWS Bedrock agents, automating workflows with Python, and creating robust observability and billing pipelines for LLM usage.
• You will be responsible for ensuring that our AI services are not only functional but also cost-effective and highly monitored through advanced logging and alerting.

Key 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 automation.

Technical Requirements (The "Must-Haves")

• 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.