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Job opening Python Gen AI Developer @ Global Data- Hyd

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Onsite

Job opening Python Gen AI Developer @ Global Data- Hyd

Globaldata

Job opening Python Gen AI Developer @ Global Data- Hyd

Skills

SQL QueriesPythonAI

2 months ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

10 August 2026

What they need


Hello,
Greetings from GlobalData- Hyd

Job Description & Requirements:
WHAT WE ARE LOOKING FOR

We are looking for a Jr/Sr python engineering &LLM capabilities to design and build production-grade python services and data pipelines. The role involves working with APIs, web-based data sources, data validation, and integrating LLMs into scalable applications.

Key Responsibilities:

  • Build and maintain Python data services and pipelines that run in scalable production systems
  • Integrate data from a range of internal and external sources, including APIs and web-based sources
  • Design pipelines that process incrementally, and handle change in upstream sources
  • Model and validate data against defined schemas, and maintain those contracts across pipeline stages
  • Apply LLMs to processing tasks that rule-based logic cannot handle well, with output constrained and validated
  • Implement validation and quality checks, including flagging records for review where confidence is low
  • Measure output quality against test sets, and monitor performance and processing cost
  • Build shared, reusable components rather than one-off solutions
  • Contribute to code review, documentation, and engineering standards

Requirements

Python and engineering

  • 3-8 years of software engineering experience, with strong production Python
  • Asynchronous and concurrent Python (asyncio with httpx or aiohttp)
  • Experience integrating and processing data from APIs and web-based sources at volume
  • Data modelling and validation using Pydantic or similar
  • Building services that run unattended: retries, idempotency, checkpointing, logging and monitoring
  • SQL and relational data
  • Git, code review, testing, and CI as standard practice

AI and LLMs

  • Hands-on experience using LLM APIs within production applications
  • Ability to obtain reliable structured output from a model and validate it downstream
  • A systematic approach to prompt development, including versioning and testing against fixed examples
  • Understanding of where model output requires verification, and how to build

Regards,

Salim- HR team

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