Sanas: Software Engineering Intern – SI & Agentic AI Platform

Job Description

The Software Engineering Intern – SI & Agentic AI Platform role at Sanas offers students an opportunity to work on production-oriented software systems supporting advanced speech intelligence and AI experiences. Sanas develops real-time speech AI technology focused on making human communication clearer and more inclusive through capabilities such as accent translation, noise cancellation, speech enhancement, and cross-language communication. During this four-month onsite internship in Bangalore, interns will receive shared onboarding across the Speech Intelligence platform and learn how calls move through different stages, from desktop applications to the Portal, Speech Communication Infrastructure, and insight-generation systems. The role is designed for students who want practical exposure to modern software engineering while working alongside engineers building AI-powered products.

Interns will be assigned a primary technical track while developing a broader understanding of the systems surrounding Sanas' Speech Intelligence platform. The internship emphasizes hands-on engineering rather than purely observational learning, with interns receiving ownership of scoped tickets across the complete development lifecycle. Depending on their track, candidates may work with Python, Go, TypeScript, React, APIs, data structures, debugging, distributed systems, data-heavy backends, or AI-related workflows. Interns can also gain exposure to technologies such as Kafka, Redis, SQL, ClickHouse, AWS S3, observability tools, LLM prompting, evaluation, natural language processing, and information extraction. This environment provides a valuable opportunity to connect academic concepts with real production engineering challenges.

A major benefit of the program is exposure to the practices used by professional product engineering teams. Interns will receive mentorship from engineers working on production Speech Intelligence and Portal features while participating in activities ranging from design and implementation to testing and code review. They can also gain experience understanding production incidents, analyzing metrics, thinking about customer-facing reliability, and documenting technical problems through concise engineering notes, pull requests, tickets, and architecture-related documentation. For students interested in software engineering, artificial intelligence, agentic AI, distributed systems, speech technology, backend development, or data engineering, this internship offers a strong opportunity to develop practical engineering judgment and contribute to a rapidly evolving AI product ecosystem.

Roles & Responsibilities

1. Contribute to Production Software
   Work on scoped engineering tickets that contribute to Sanas' Speech Intelligence and Portal products while following the team's development, testing, review, and deployment practices.
2. Understand Speech Intelligence Systems
   Participate in onboarding and develop a practical understanding of how calls move from desktop applications through the Portal, Speech Communication Infrastructure, and downstream insight systems.
3. Develop Software Features
   Design and implement assigned software functionality using technologies such as Python, Go, TypeScript, or React, depending on the intern's primary technical track.
4. Work with APIs and Integrations
   Develop or support API-based functionality and learn how different components communicate within a production software ecosystem.
5. Debug Technical Issues
   Investigate software defects and unexpected system behavior, use debugging techniques to identify root causes, and implement appropriate fixes under engineering guidance.
6. Work with Data Systems
   Gain practical exposure to SQL, Redis, Kafka, analytics databases, or ClickHouse while working with data-heavy backend systems and understanding how information moves through production applications.
7. Explore AI and NLP Workflows
   Depending on the assigned track, contribute to activities involving LLM prompting, evaluation, information extraction, regex-based NLP, or other AI-related application workflows.
8. Participate in Testing and Code Reviews
   Test assigned implementations and participate in pull-request reviews, incorporating engineering feedback to improve code quality, maintainability, reliability, and correctness.
9. Monitor Production Reliability
   Develop awareness of production incidents, application metrics, observability practices, and customer-facing reliability while learning how engineering teams respond to operational challenges.
10. Write Technical Documentation
    Prepare concise technical notes, tickets, pull requests, and issue documentation that clearly communicate implementation details, problems, decisions, and potential solutions.
11. Collaborate with Engineering Teams
    Work closely with experienced engineers, ask relevant technical questions, communicate progress, and incorporate mentorship and feedback into day-to-day development activities.
12. Own Assigned Tasks End-to-End
    Take responsibility for scoped work from initial design and implementation through testing, review, refinement, and completion while maintaining a high standard of engineering quality.

Requirements & Eligibility

1. Pursuing a Relevant Degree
   Candidates should be pursuing a BS or MS in Computer Science, Electrical Engineering, Data Science, or a related technical discipline. Equivalent practical experience may also be considered.
2. Programming Skills
   Applicants should have solid programming ability in at least one relevant technology, including Python, Go, or TypeScript/React, and should be comfortable applying programming concepts to practical software problems.
3. API Knowledge
   Candidates should understand fundamental API concepts and how software components communicate, with an ability to work with APIs as part of application development and integration tasks.
4. Data Structures Understanding
   A sound understanding of data structures and fundamental problem-solving concepts is important for developing efficient and maintainable software solutions.
5. Debugging Ability
   Candidates should be comfortable investigating errors, tracing unexpected behavior, analyzing logs or application output, and systematically working toward technical solutions.
6. Interest in Distributed Systems
   Curiosity about distributed systems, AI products, backend infrastructure, or data-intensive applications is valuable for succeeding in an environment involving modern production technologies.
7. Database and Messaging Exposure
   Familiarity with technologies such as Kafka, Redis, SQL, or analytics databases is beneficial. Experience with ClickHouse can provide additional value for data-intensive engineering work.
8. AI and NLP Knowledge
   Exposure to LLM prompting, AI evaluation, natural language processing, regex-based NLP, information extraction, or related AI concepts is considered an advantage.
9. Cloud and Observability Awareness
   Basic familiarity with cloud technologies such as AWS S3 and application observability tools can help candidates understand production environments and modern cloud-based engineering workflows.
10. Communication and Project Experience
    Candidates should communicate clearly in technical notes, tickets, pull requests, and team discussions. Previous internships or strong personal projects with publicly demonstrable GitHub work can strengthen an application.

Expected Salary

For a Software Engineering Intern in Bangalore, a realistic market-oriented internship stipend is approximately ₹20,000–₹50,000 per month, with the actual amount varying significantly based on the startup, technical specialization, candidate profile, and internship program. AI-focused startups and candidates with strong software engineering or machine learning project experience may fall toward the higher end of this range.

Because Sanas is a specialized AI product company and the internship involves production software, distributed systems, and Speech Intelligence technologies, the actual stipend may differ from the general Bangalore internship market. Candidates should treat this range as an indicative estimate rather than a confirmed Sanas compensation figure.

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