Job Description

Important note: This role requires consistent presence every week in the office, in Pune.

About the Role

We are looking for a strong software engineer who actively uses AI to build better software faster. This is a backend-heavy engineering role where LLMs and AI systems are integrated into real production applications.

You will design, build, deploy, and maintain AI-enabled systems, while maintaining strong engineering discipline and code quality.

Key Responsibilities

Architect and build scalable backend systems (Python / FastAPI preferred)
Integrate LLM APIs, RAG pipelines, and AI workflows into production applications
Deploy and maintain containerized applications on AWS/Azure
Use AI coding assistants and agents to accelerate development, without compromising code quality
Convert ambiguous requirements into production-ready systems

Must-Have Skills

4+ years of professional software engineering experience
Strong Python backend experience
Experience building REST APIs and production systems
Solid understanding of system design and clean architecture
Hands-on experience with Docker and Linux
Experience deploying to AWS or Azure
Experience integrating LLM APIs into applications
Experience with embeddings / vector databases / RAG pipelines
Strong Git and collaborative development workflows
Ability to operate independently in ambiguous environments

Most importantly:

Strong engineering fundamentals
High ownership mindset
Comfort using AI tools to move fast
Discipline to maintain structure and quality

Good-to-Have

Experience with real-time streaming or WebSockets
Kubernetes deployment experience
Experience in a fast-paced startup or consulting environment
Familiarity with agent frameworks or voice/multimodal systems

Screening Requirement

Please include:

A portfolio of systems you’ve built (especially AI-enabled systems), and
A short note explaining how you use AI tools in your development workflow.

We are specifically looking for engineers who lean into AI agents and coding assistants, but still understand architecture, performance, and clean code.