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.
