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Python AI Developer

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Hybrid

Python AI Developer

Nexon Software Solutions

Python AI Developer

Skills

DockerDjangoFlaskPythonAIAWSKubernetesFastAPI

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹3,000,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

11 August 2026

What they need


Hi

JD

Senior Software Engineer (Python + AI)

Chennai, Bangalore, Hyderabad, Gurugram (Hybrid) Weekly 2 days

6 10 YRS

The role appears to be:

60-70% Backend Engineering (Python)

20-30% AI/LLM Platform Development

10-20% System Design, Reliability, and Collaboration

ABOUT YOUR ROLE

We're hiring Senior Software Engineers to join our AI-native engineering team. You'll design, build, and operate production AI systems - including AI platform capabilities, agentic workflow infrastructure, and LLM-powered features that serve institutional financial clients. This is a hands-on individual contributor role for engineers who are deeply fluent in AI-native development and want to work at the intersection of applied AI and backend systems engineering.

WHAT YOU'LL DO

Build and Operate AI Systems

* Design, build, and ship production-quality backend services, APIs, and AI platform components used across multiple engineering teams

* Build and integrate LLM-powered systems such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, prompt/tool orchestration, and model observability

* Improve the reliability, scalability, observability, and operational quality of production AI systems

* Build internal tools, frameworks, automation, and documentation that improve developer productivity and AI capabilities

* Participate in code reviews, design reviews, debugging, incident response, and operational support

Drive Technical Excellence

* Contribute to technical design for complex projects, including evaluating tradeoffs and proposing pragmatic implementation plans

* Partner with product, design, and engineering teams to translate platform needs into well-designed technical solutions

* Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle

* Collaborate with Staff and senior engineers to establish reusable patterns and raise engineering standards

Build with AI-Native Practices

* Use agentic coding tools and LLM-assisted development as a primary part of your workflow this is how the entire team operates

* Critically evaluate AI-generated code for correctness, edge cases, and regressions — shipping quality output regardless of how it was produced

* Contribute to the team's evolving practices around AI-accelerated development and testing

QUALIFICATIONS

Required

* 5+ years of experience designing, building, and operating production software systems

* Strong backend engineering experience with Python frameworks such as FastAPI, Flask, or Django

* Experience building or integrating AI/LLM-powered systems in production - such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, or agentic workflows

* Experience with relational/NoSQL databases, including schema design, query optimization, and data modeling

* Experience with cloud-native technologies such as AWS, Docker, and Kubernetes

* Strong understanding of CI/CD, observability, and operating services in production

* Ability to break down complex technical problems and deliver pragmatic, maintainable solutions

* Strong ownership mindset, with the ability to drive projects independently while collaborating effectively

* Clear communication skills and the ability to explain technical tradeoffs to engineering and cross-functional partners

* Hands-on experience with AI-native development tools (e.g., Cursor, Augment); demonstrated ability to embed AI-driven practices to accelerate velocity and code quality

* Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases

Preferred

* Experience with document processing pipelines, structured extraction from unstructured documents, or vector stores

* Familiarity with evaluation frameworks for LLM output quality (e.g., RAGAS, custom evals, human-in-the-loop review)

* Background in financial services or fintech

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