Senior Software Engineer (AI PYTHON)

Bounteous; India; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Bounteous in India is seeking a Senior Software Engineer to join our AI-native engineering team. You will design, build, and operate production AI systems including AI platform components and LLM-powered features for enterprise clients.

This hands-on role requires deep fluency in AI-native development, strong backend skills in Python, and experience with AWS, Docker, and Kubernetes. You will collaborate across product and design to deliver reliable, scalable software.

Qualifications

• 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.

Responsibilities

• Design, build, and ship production-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.
• 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.
• Use agentic coding tools and LLM-assisted development as a primary part of your workflow – this is how the entire team operates.

Skills

Python frameworks

AWS

Docker

Kubernetes

Backend engineering

AI-native development

Tools

Cursor

Augment

Job description

5 to 7 years of experience

Skills: Python frameworks, AWS, Docker, Kubernetes

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.

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