Founding Backend Engineer

At Stimuler, we're building Speech AI models to empower the next 2 Bn+ Non-Native English speakers to enhance their conversational skills.

Our AI tutor provides real-time interaction, adapting to users’ speech inputs to build fluency faster.

We’re looking for a Founding Backend Engineer to work directly with the CTO to architect and scale our core infrastructure.

This is a critical early role, and you'd be a part of the core engineering team.

In terms of scale, we currently have over 4Mn+ app installs and over $100k in monthly revenue (90%+ of which is outside India) and aim to scale 10x from here in the next 12 months.

We are backed by Lightspeed and a bunch of top investors from Singapore, Japan, and India.

Role & Impact In this role, you will design, develop, and maintain the backend systems that power our AI tutor.

You’ll work at the intersection of AI infrastructure, distributed systems, and real-time data processing—shaping the technology and the team as we grow.

Top percentile comp : 25-40 LPA Base + Significant ESOPs (in a fast growing pre-series A startup) + benefits Key Responsibilities ---Infrastructure & Architecture Design and scale distributed systems for real-time speech processing.

Own data pipelines from ingestion to model serving.

Ensure security, privacy, and compliance for user speech data. --- Performance & Reliability Implement robust monitoring, logging, and alerting for 24x7 availability.

Optimize system performance and scalability.

Must-Have Requirements Experience : 2-5+ years in backend or platform engineering (focus on distributed systems).

Cloud & Containers : Proficiency with Kubernetes and AWS (or similar cloud platforms).

Real-Time Streaming : Familiarity with audio/video streaming in high-availability, auto-scaling environments.

Databases : Strong SQL skills (PostgreSQL preferred), including query optimization, schema design; caching layers (Redis, Memcached). ps: Evidence of high ownership in complex engineering projects is something we place a big emphasis on.

If you have tried building something of your own, that's a great bonus too.

Good-to-Have Skills AI/ML Pipeline : Exposure to GPU resource management and distributed tools (e.g., Rayserve).