How to Get a Job at Sanas: Interview Process, Experience & Tips (2026)

Sanas builds real-time AI that neutralises accents and removes background noise on live calls, helping BPO agents and customer-support teams sound clear and confident. The product targets enterprise clients in voice-heavy industries, and the company has grown by signing deals with large contact-centre operators globally.

As of mid-2026, Sanas carries around 10 open roles spanning engineering, go-to-market, and operations. Because the team is still relatively compact, each new hire is expected to contribute quickly and own a meaningful slice of the work from day one. Competition for these seats is real, but the upside is direct exposure to senior leadership and visible impact fast.

For Indian professionals with a background in AI, speech technology, enterprise SaaS sales, or BPO operations, Sanas represents an unusual opportunity: a product that was literally built to serve the experience of non-native English speakers in high-volume call environments.

Most candidates report a process that runs roughly four to five rounds, though the exact shape varies by role and team. The stages you can generally expect are described below.

Recruiter or HR screen. A talent partner checks your background, clarifies the role, and asks what draws you to voice AI. Be ready to explain why Sanas specifically interests you, not just AI in general. This call is also your chance to ask about the working model and team structure.

Hiring-manager interview. The manager digs into your past projects, your problem-solving style, and how you have handled ambiguity. For technical roles, expect a conversation around system design or ML concepts. For business roles, expect questions on pipeline management, customer conversations, or go-to-market strategy.

Technical or skills round. Engineering candidates typically face a coding exercise or a take-home assignment focused on signal processing, backend services, or ML inference. Non-engineering candidates may be asked to present a case study or walk through a past deal or campaign in detail.

Panel or cross-functional round. You meet two or three colleagues from different teams. The goal is to test communication, collaboration, and whether you can hold your own in a fast-moving conversation across disciplines. Expect at least one person in this panel to push back on something you say.

Final conversation or reference check. This may involve a co-founder or senior leader. Expect questions about where voice AI is headed and how you see your role in shaping it. References are usually checked around this stage.

Timelines are not always predictable at a startup of this size. Following up politely after each round is perfectly acceptable and signals genuine interest.

Sanas looks for people who combine technical depth with a genuine curiosity about voice AI and the real-world challenges of deploying it at scale. A few themes come up consistently across roles.

Ownership mindset. Because the team is small, there is no room for people who wait to be told what to do next. Interviewers probe for examples where you spotted a problem, took initiative, and followed through without heavy supervision.

Comfort with ambiguity. The product roadmap shifts as enterprise customers give feedback. They want people who can make a sound decision with incomplete information and course-correct quickly rather than waiting for perfect clarity.

Communication across functions. Engineers need to explain their work to sales and customer-success teams. Business folks need to understand enough of the technology to have credible conversations with CTOs and IT heads. Strong written and verbal communication is valued across all roles.

Domain relevance. Prior exposure to speech, audio, NLP, or real-time AI systems is a plus for technical roles. For go-to-market roles, experience selling to enterprise clients in SaaS, BPO, or contact-centre software stands out. Neither is an absolute requirement, but both signal a faster ramp-up.

Collaboration and humility. Early-stage companies look for people who are confident in their skills but open to feedback. Arrogance is a red flag when everyone needs to learn from each other daily.

Understand the product before your first call. Use the Sanas website, watch any public demos, and read recent news about real-time voice AI. Being able to speak intelligently about why accent neutralisation matters for BPO agents, and what the competitive landscape looks like, signals genuine interest rather than a spray-and-pray application.

Prepare three to four strong STAR stories. Sanas interviewers lean on behavioural questions. Have concrete examples ready for: leading a project under pressure, handling a technical setback, collaborating with a difficult stakeholder, and delivering results with limited resources. Each story should have a clear outcome you can quantify or describe precisely.

Brush up on relevant fundamentals. For engineering roles, review real-time audio processing, low-latency inference, and distributed systems basics. For ML roles, be comfortable discussing model compression, streaming inference, and evaluation metrics for audio models. For sales roles, practise a crisp 'pitch-back' of the Sanas value proposition to a sceptical VP of Operations.

Research the competitive landscape. Voice AI is a crowded space. Knowing the difference between Sanas and broadly similar tools shows you have done your homework. Frame it around where Sanas wins, not just that competitors exist.

Prepare thoughtful questions for each round. Good questions show engagement. Ask about the biggest technical challenges the team is solving this quarter, how they measure success for this role in the first few months, and how the team makes product decisions. Avoid asking questions answered clearly on the website.

Tailor your resume before applying. Highlight any experience with voice, audio, real-time systems, enterprise sales cycles, or BPO and contact-centre clients. A targeted resume moves through initial screening faster. knok checks 150+ job sites nightly, applies to matching roles on your behalf, and messages HR directly, so your application stays visible even while you are deep in preparation.

Sanas operates with the pace and intensity typical of a venture-backed AI startup. A few cultural traits stand out based on what the company communicates publicly and what candidates commonly describe after going through the process.

Mission-first thinking. The founding idea, that a person's accent should never limit their professional opportunities, carries real emotional weight inside the company. Employees are expected to connect their day-to-day work back to that mission, whether they are writing code or closing a deal.

High accountability. In a small team, there is nowhere to hide. People own their outcomes, and that accountability is expected at every level. This creates a culture where direct feedback is normal and slow follow-through is noticed quickly.

Cross-functional collaboration. Engineering, product, and go-to-market teams work closely together. Decisions are made quickly, sometimes in short syncs rather than long planning cycles. If you prefer siloed, heavily structured environments, the pace here may feel uncomfortable at first.

Openness to new ideas. Because the product is still evolving, the company tends to welcome fresh thinking about how to improve the model, grow into new markets, or serve customers better. People who bring ideas and back them with data tend to earn influence early.

Global and inclusive mindset. Serving BPO markets means the team thinks globally from day one. There is typically a mix of backgrounds and a sensitivity to how language and communication shape professional experience, which is especially relevant for Indian professionals joining the team.