Software Engineering Intern - SI & Agentic AI Platform
📄 Job Description
About Sanas
Sanas is pioneering the future of human communication with the world's first real-time speech AI platform, capable of accent translation, noise cancellation, and cross-language communication. Founded by Stanford researchers, Sanas is one of the fastest-growing startups in Silicon Valley, projecting significant ARR growth. The company has secured over $100 million in funding from leading investors like Insight Partners and Google Ventures, solidifying its reputation through collaborations with Fortune 100 companies.
About the Role
Sanas is hiring four Software Engineering Interns for a four-month, onsite opportunity in Bangalore. Each intern will have a primary track and will receive shared onboarding on the Speech Intelligence platform to understand the end-to-end call processing flow from desktop to insights.
Requirements
Required Qualifications
- Currently pursuing a BS/MS in Computer Science, Electrical Engineering, Data Science, or a related field (or equivalent experience).
- Solid programming proficiency in at least one of: Python, Go, or TypeScript/React.
- Comfortable with APIs, data structures, and debugging.
- Curiosity about distributed systems, AI products, or data-heavy backends.
- Clear written communication skills (e.g., for short notes, PRs, tickets).
Nice to Have
- Experience with message queues (Kafka), Redis, SQL, or analytics databases (ClickHouse is a plus).
- Familiarity with LLM prompting/evaluation, regex NLP, or information extraction.
- Basic understanding of cloud platforms (AWS S3, observability tools).
- Prior internship experience or a strong portfolio of personal/project work on GitHub.
What You Will Gain
- Mentorship from engineers shipping production Speech Intelligence and Portal features.
- Ownership of scoped tickets from end-to-end (design, code, test, review).
- Exposure to real production incidents, metrics, and customer-facing reliability challenges.
- Practical experience in writing technical documentation and architecture notes, mirroring team standards.
