Key Responsibilities :

1. Product & Technology Architecture :

- Own the end-to-end architecture and technology roadmap.

- Define scalable, secure and modular architecture for video interviewing, AI interviewing, candidate assessment and recruiter workflows.

- Design AI/ML architecture covering LLMs, speech-to-text, NLP, conversational AI, RAG, multimodal AI and AI-based evaluation.

- Define architecture for real-time and asynchronous video/audio processing.

- Drive API-first, microservices and cloud-native architecture.

- Ensure scalability, availability, observability and performance for enterprise workloads.

2. Product Management :

- Translate customer/business requirements into product capabilities, architecture and roadmap.

- Own/drive product backlog, feature prioritization and release planning in partnership with Product/Business teams.

- Conduct competitive benchmarking against platforms such as HireVue, Spark Hire and other AI interviewing platforms.

- Identify product gaps and define capabilities required to make products enterprise and market competitive.

- Balance build vs. buy vs. integrate decisions for AI, video, communication and assessment components.

3. AI & Video Interviewing :

- The candidate should have strong understanding of :

- AI interviewer / conversational AI

- Dynamic and adaptive interview questioning

- Job Description + Resume-based question generation

- Speech-to-text and multilingual transcription

- LLM-based interview summarization

- Competency-based scoring and evaluation

- Video/audio intelligence and multimodal AI

- Interview scorecards and structured evaluation

- AI-driven candidate ranking and recommendations

- Anti-cheating / interview integrity capabilities

- Human-in-the-loop AI evaluation

4. Enterprise Platform Capabilities :

- Drive architecture/productization of :

- Multi-tenancy and tenant isolation

- RBAC and enterprise identity integration

- API gateway and partner integrations

- ATS / HRMS integrations

- Interview scheduling and notifications

- Candidate and recruiter portals

- Analytics and dashboards

- Audit trails and data lineage

- Consent, privacy and data retention

- Security and compliance

- Monitoring, SLA and production support architecture

5. Product Engineering Leadership :

- Work closely with Engineering, AI/ML, UX, QA, DevOps and Product teams.

- Establish architecture standards and technical governance.

- Review technical designs and ensure engineering alignment with product roadmap.

- Mentor architects and senior engineers.

- Drive technical debt reduction and platform modernization.

Required Skills :

Architecture :

- Distributed systems / microservices

- Cloud-native architecture AWS/Azure/GCP

- REST APIs, event-driven architecture and API gateways

- Databases, caching, messaging and data platforms

- Kubernetes / containers

- CI/CD, observability and SRE principles

AI :

- LLMs and GenAI

- RAG and vector databases

- Conversational AI / AI Agents

- NLP and speech technologies

- Multimodal AI

- AI evaluation and model governance

Video / Communication :

- WebRTC or equivalent real-time video technologies

- Video/audio streaming and processing

- STT/TTS

- Recording, storage and media pipelines

- Experience with Twilio, Vonage or equivalent communication platforms is desirable.

Product :

- Product lifecycle management

- Product roadmap and prioritization

- Agile/Scrum

- Customer discovery

- Competitive analysis

- Build vs. buy decisions

- Enterprise SaaS product management

Preferred Experience :

- Candidates from AI-powered HRTech, Video Interviewing, Assessment, Recruitment SaaS, Conversational AI or Enterprise SaaS platforms will be preferred.

- Experience working on products comparable to HireVue, Spark Hire, VidCruiter, Modern Hire or other AI/video interviewing platforms would be highly valuable.

Key Success Measures :

- Define the product and technology roadmap.

- Build scalable architecture supporting enterprise customers and high-volume interviews.

- Establish strong AI evaluation, security, privacy and governance capabilities.

- Identify competitive gaps and convert them into prioritized product capabilities.

- Reduce dependency on fragmented third-party components through a clear build/buy/integrate strategy.

- Work across Product + Engineering + AI/ML + Business and drive execution.