ClearGrid is an AI-native debt resolution platform operating across the UAE and Saudi Arabia. Our AI voice agents handle borrower conversations at scale in Arabic and English for leading banks and NBFIs running on infrastructure we built in-house.
This is one of the largest production deployments of conversational voice AI in the region. Real regulated clients real volume and real consequences when a call goes wrong. Were past the demo stage and deep into the harder problem: making voice AI reliable affordable and scalable.
Were hiring a Product Manager to own our Voice AI product end to end.
This is a high-autonomy high-visibility role for someone equally comfortable debating voice model budgets and model trade-offs with engineers as they are shaping roadmap and working with commercial teams and bank clients. Youll own three things that are currently unowned: the performance and cost of the voice stack the tooling our prompt engineers depend on every day and the evolution of the platform into something clients can configure and monitor themselves.
You will be the single owner of Voice AI at ClearGrid its quality its economics and where it goes next.
Voice AI Stack Performance
Own end-to-end performance of the voice product: quality latency transcription accuracy (Arabic and Gulf dialects especially) interruption handling and conversational reliability. Work with engineering to instrument monitor and improve it continuously.
Voice Infrastructure & Capacity
Own the stack: STT TTS model routing telephony gateways dialing and redial capacity. Forecast capacity against volume so constraints surface in planning not in production.
Cost & Efficiency
Own the unit economics of voice: cost per minute cost per connected call. Build a defensible model track it and drive it down without sacrificing quality. Make build/buy and vendor decisions with data behind them and find ways to serve a wider range of client budgets.
Prompt & Agent Platform
Own the tooling our prompt engineers depend on. Today every AI agent across lenders products delinquency stages and languages is authored versioned tested and deployed by hand. Youll turn that into a product: a central agent library version history and rollback automated pre-deployment validation and regression testing against real call scenarios. The measure is simple: how fast we can launch a new agent and how fast we can fix a live one.
Production Quality
Own how we detect and prevent failures in live agents. Our clients are regulated financial institutions; a bad call is a compliance event not a bug. Build the QA and monitoring loop that catches issues systematically rather than relying on someone listening to calls after the fact.
Client-Facing Platform
Lead the evolution of the voice platform into a product lenders can use directly: agent setup and configuration campaign controls performance analytics call recordings and transcripts QA evidence. Reduce the manual work that currently sits between a client request and a client answer.
Product Discovery
Track the voice AI market closely. Evaluate new models and capabilities decide which languages and models we support and know when something better has shipped.
Stakeholder Ownership
Own intake prioritization and delivery for everything voice. Work daily with prompt engineers engineering analytics QA compliance and the collections floor and be willing to say no to protect the roadmap.
46 years of product management experience shipping software with engineering teams.
Hands-on voice AI experience: voice agents speech models or voice-based products: strongly preferred. Well also seriously consider strong conversational AI / LLM application contact centre or speech backgrounds where the technical depth is clearly there.
Experience owning an internal tooling or workflow product for expert users. Youll be building for our own prompt engineers and thats a distinct skill from client-facing product work.
Comfortable owning a cost line. You can build and defend a unit economics model and drive cost per unit down without degrading quality.
Data-literate. You pull and interrogate your own data rather than waiting for a dashboard.
A technical foundation (computer science or similar) is a plus though hands-on experience matters more than formal qualifications.
Experience shipping Arabic or other non-English language products is a strong plus. Arabic fluency is a plus but not required; English fluency is.
Experience with regulated or enterprise clients financial services especially is a plus.
A systems thinker: hands-on proactive and comfortable operating with ambiguity.
An excellent communicator who can flex between an engineering standup and a bank steering committee.
Genuine enthusiasm for AI and emerging technology: someone who stays current on the space out of curiosity not obligation.
In 3 months: Youve mapped the voice stack and the prompt engineering workflow established baselines for deploy time fix time and cost per connected call and agreed a Phase 1 roadmap.
In 6 months: Manual prompt engineering effort is measurably down. A cost-per-connected-call reduction plan is documented and in execution. Client-facing setup and analytics are live with at least one lender.
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