Voice Designer

Rifa AI is building the AI agents platform for contact centers in regulated industries.

Enterprises in these industries want AI agents handling their customer operations and mostly can't deploy them. It's not a model problem. Horizontal platforms lack governance, release processes, and change management, and in a domain where every call can be reviewed by a regulator, that's disqualifying. Building an AI agent has never been easier. Deploying one an enterprise can trust has never been harder. That harder problem is the one we work on.

Our platform turns a company's written procedures into AI agents: voicebots that hold real-time conversations, take actions in the client's CRM, and stay within the limits the client has set. Every release is gated by an automated testing suite, and every conversation feeds a post-analysis platform. We're live in production today, handling debt collection calls for US financial services clients.

The engineering convictions behind it: evaluation methodology, not model capability, is the bottleneck. Every rule and decision trace becomes part of a company's context graph. Observability goes beyond logging. And our Agent Studio lets engineers, non-engineers, and auditors collaborate to build and improve AI agents with the right guardrails to achieve the expected business outcomes.

Rifa was founded by Sameer Fulzele (IIT Bombay). We're a small team of exceptionally capable, passionate engineers with paying enterprise clients and growing revenue, backed by Seaborne Capital, a founder-first firm of exceptional industry operators that works closely with its founders, and by angel investors who are veterans of enterprise software and operators in the accounts receivable industry.

Our agents phone people about overdue accounts. It is not a friendly context, and the voice carries more of the load than anyone expects: it has to sound like a person, hold steady when the other side gets angry, and read a required disclosure without sounding like a recording of a lawyer.

Nobody here owns that today. Engineers pick whichever voice the TTS provider offers and move on, and you can hear it on the calls. We want someone whose actual job is how Rifa sounds in US English.

Most of your first few months goes on US English voices for live collections calls. The rest goes on making the work repeatable, so the next locale is easier than this one.

• Start with the compliance language. Every call carries wording that has to come out verbatim. Engineering guarantees the words are right. You decide whether they land as information or as a threat, and that decision shows up in whether people stay on the line. Most candidates underrate this part of the job.

• Design the voices. Accent, pace, where the stress falls, how long a pause can run before it reads as hesitation. These are judgement calls, and you will have to defend them to a client who asks for "warmer" and cannot say what warmer means.

• Work in the pipeline. Voice config lives in the repo. You will edit it, run it, listen, adjust, open a PR. We are not building you a GUI for this, so you will need to be comfortable in a terminal. When you hit the limits of the tooling, say so precisely; vague complaints do not get fixed.

• Cast and record. Find voice actors, direct the session, then do the unglamorous half: cutting, cleaning and prepping takes until the pipeline can use them.

• Give us a way to argue about quality with evidence. Today "does this sound good" gets settled by whoever feels strongest about it. Naturalness, intelligibility down a bad phone line, whether a voice drifts over a twelve minute call: pick what actually matters and get it into the eval suite that already gates our releases.

Your ear and your portfolio matter more here than your job titles.

• You have worked professionally on how things sound. Sound design, audio post, music production, game or interface audio: somewhere it counted.

• You can record and edit speech yourself. Directing a nervous actor into a usable read, and salvaging a take from a room with a fridge in it.

• A real ear for American English. Not just hearing that an accent exists, but being able to say why one read works on a collections call and another sounds like a telemarketer.

• You are fine in a terminal. Scripts, config files, git, AI coding tools. Nobody expects you to write the synthesis code.

• Something we can listen to.

• Enough overlap with US afternoons to join client calls. In practice that means some evenings on IST.

• TTS or voice cloning work: SSML, prosody controls, ElevenLabs and similar.

• You know what 8 kHz narrowband does to a voice you spent a week on.

• Somewhere tone had consequences: healthcare, financial services, a crisis line.

• Another locale you would want to take on next. US English is only where we start.

Small teams per client, with real ownership. We review each other's work, we write things down, and we'd rather hear an honest "I don't know yet" than a confident wrong answer.

• Trust: We do the right thing, especially when nobody is checking. Clients hand us regulated conversations with their own customers, and we earn that every day.

• Transparency: We write things down, share the real numbers, and say "I don't know yet" out loud, with each other and with clients.

• Technically best solution: We choose what's right, not what's easiest or trendiest. When we notice we got it wrong, we fix it.

• Decisiveness: We decide quickly with the information we have, commit, and correct course fast when reality disagrees.

• Simplicity: We keep systems, processes, and words simple. Complexity is a cost we pay only when it clearly buys something.