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Salary
≈ $22k – $50k per year (Estimated)
Location
In office (Pune)
Experience
12+ years exp

First seen by Alion on Oct 13, 2026.

Overview
Company
Impact
Profile match
Zorba Consulting is a data science and AI consulting firm that helps companies bring data into their decisions. It staffs data architects, data scientists, full stack developers and Databricks engineers on client projects in cities such as Bengaluru, Hyderabad, Chennai and Pune. The company is headquartered in Bengaluru, India.

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 :

- 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.

Work Location :

Pune (Onsite requirement : 4 days/week)

Skills

Cloud Services, AIOps, IT Infrastructure, Python, IT Automation, Observability Services, AWS, AWS Bedrock, Monitoring Tools, Generative AI

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