This role is ideal for someone who combines strong engineering leadership with deep AI product-building experience, someone who can code, lead, and innovate at the same time. The CTO will manage the engineering team, guide AI development, interface with clients for technical requirements, and ensure scalable, reliable delivery of all Voiceoc platforms.

Responsibilities :

- Own end-to-end architecture, development, and deployment of Voiceoc's AI-driven Voice & Text platforms.

- Work closely with the Founder to define the technology roadmap, ensuring alignment with business priorities and client needs.

- Oversee AI/ML feature development, including LLM integrations, automation workflows, and backend systems.

- Ensure system scalability, data security, uptime, and performance across all active deployments (US Projects).

- Collaborate with the AI/ML engineers to guide RAG pipelines, voicebot logic, and LLM prompt optimisation.

- Actively contribute to the core codebase (preferably Python/FastAPI/Node).

- Lead by example in code reviews, architecture design, and debugging.

- Experiment with LLM frameworks (OpenAI, Gemini, Mistral, etc. ) and explore their applications in healthcare automation.

- Manage and mentor an 8-10 member engineering team.

- Conduct weekly sprint reviews, define coding standards, and ensure timely, high-quality delivery.

- Hire and train new engineers to expand Voiceoc's technical capability.

- Foster a culture of accountability, speed, and innovation.

- Join client calls (US-based hospitals) to understand technical requirements or resolve issues directly.

- Collaborate with the founder on technical presentations and proof-of-concept discussions

- Handle A-Z of tech operations for the US business infrastructure, integrations, uptime, and client satisfaction.

Requirements :

- 5- 7 years of experience in software engineering with at least 2+ years in a leadership capacity.

- Strong proficiency in Python (FastAPI, Flask, or Django).

- Experience integrating OpenAI / Gemini / Mistral / Whisper / LangChain.

- Solid experience with AI/ML model integration, LLMs, and RAG pipelines.

- Proven expertise in cloud deployment (AWS / GCP), Docker, and CI/CD.

- Strong understanding of backend architecture, API integrations, and system design.

- Experience building scalable, production-grade SaaS or conversational AI systems

- Excellent communication and leadership skills capable of interfacing with both engineers and clients.