Python Developer New

Neev Systems; Hyderabad; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

Neev Systems in Hyderabad is seeking an experienced Python professional to lead technically and operate independently on complex data systems. You will design end-to-end pipelines, manage high-throughput platforms, and work with Pandas, NumPy, and Polars.

The role covers REST services, relational databases, Linux, AWS, and Docker, with opportunities to integrate LLMs and AI services into internal tools. You will drive AI-assisted development, optimize large codebases, and contribute to scalable,

Qualifications

• 5+ years Python development with independent and leadership experience.
• Experience designing systems and building non-trivial pipelines end to end.
• Designing, building, operating high-throughput data calculation platforms.
• Familiarity with Pandas, NumPy, and Polars.
• Experience with REST services, SQL databases, Linux, and cloud/docker.
• Integrate AI services and LLMs into internal apps and APIs.
• Fluent in AI-assisted development and automation workflows.
• Ability to read, review, optimize, and refactor large codebases.

Skills

Python

Data pipelines

High-throughput data platforms

Pandas

NumPy

Polars

REST APIs

Relational databases

SQL

Linux

AWS

Docker

LLMs integration

AI services

Vector databases

Retrieval-augmented generation

AI-assisted development

Codebase refactoring

Engineering best practices

Tools

Pandas

NumPy

Polars

REST APIs

SQL databases

Linux

AWS

Docker

LLMs

Job description

• At least 5+ years Python, with a track record of operating independently and leading technically.
• Proven experience designing systems and building non-trivial pipelines and workflows end to end.
• Designing, building, and operating high-throughput data calculation platforms.
• Deep familiarity with data-intensive packages like Pandas, NumPy, and Polars.
• Experience building REST services, managing relational/SQL databases, working inside Linux environments, and deploying cloud/containerized infrastructure (AWS, Docker).
• Integrate LLMs and AI services into internal applications using APIs, orchestration frameworks, vector databases, and retrieval-augmented generation where appropriate.
• Fluent in AI-assisted development. Ability to integrate AI capabilities into existing services, internal tools, and automation workflows.
• Comfortable reading, reviewing, optimizing, and refactoring large codebases against sound engineering practices.