VP Engineering — AI Platform & Infrastructure

We’re looking for a VP of Engineering to lead the development, architecture, and reliability of our Enterprise SaaS platform for AI Digital Human and Conversational AI applications.

This is a hands-on role. You will be expected to code, design architecture, manage cloud and DevOps practices, troubleshoot production issues and mentor junior developers.

Key Responsibilities

• Lead the architecture and development of scalable and secure Enterprise SaaS applications.
• Develop and maintain backend services using Node.js, TypeScript, Express.js or NestJS.
• Design APIs, integrations, databases, and cloud infrastructure.
• Manage deployments and infrastructure across AWS and GCP.
• Establish strong CI/CD, monitoring, logging, and DevOps practices.
• Monitor production systems using AWS CloudWatch, Datadog, and similar tools.
• Troubleshoot application, infrastructure, database, and performance issues.
• Manage and optimise MySQL databases.
• Integrate LLMs, RAG, vector databases, STT/TTS, and Voice AI services.
• Conduct code reviews and mentor junior and mid-level developers.
• Define engineering standards for security, scalability, code quality, and reliability.

Required Skills & Experience

• 8–10+ years of software engineering experience, primarily in backend, platform, or Enterprise SaaS development.
• At least 5 years in a technical lead, engineering lead, or similar leadership role.
• Strong hands-on experience with Node.js, TypeScript, Express.js or NestJS.
• Strong experience building and operating Enterprise SaaS platforms.
• Good understanding of SaaS architecture, APIs, distributed systems, and backend design.
• Strong experience with GCP and/or AWS.
• Solid DevOps experience including Docker, CI/CD, deployment, monitoring, logging, and incident management.
• Experience with AWS CloudWatch, Datadog, or similar observability tools.
• Strong knowledge of MySQL and database optimisation.
• Experience with Git, code reviews, testing, and software engineering best practices.
• Experience leading and mentoring engineering teams.
• Willing and able to code regularly and remain technically hands-on.

Good to Have

• Experience with Kubernetes, Terraform, Redis, message queues, or WebSockets.
• Experience with multi-tenant SaaS architecture and enterprise security.
• Experience with LLMs, RAG, AI Agents, Chatbots, Voicebots, or Digital Human applications.