Responsibilities

Hands-on Technical Implementation, Architecting, and Oversight

Design and implement end-to-end systems: Guide and implement the AI-Native platform of Verneek, as well as its solution suite, fullstack: from backend infrastructure to data ingestion, model training and inference, to front-end interfaces and applications.
Architect scalable solutions: Ensure the development of robust, scalable, secure, and maintainable full-stack systems that can deploy and run AI models in production at scale.
Evaluate and select technology: Assess and recommend the use of appropriate AI frameworks (e.g., PyTorch, TensorFlow), cloud platforms (e.g., AWS, Azure), and other tools and vendors.
Enforce best practices: Drive and enforce coding standards, technical architecture patterns (e.g., microservices), and quality control mechanisms.

Strategic leadership and overall vision

Define and execute the technology strategy: Set the vision, roadmap, and strategic priorities for how Verneek’s fullstack technologies will create business value, improve products, and drive operational efficiency.
Align with business objectives: Collaborate with senior leadership and product teams to translate business needs into technical specifications and viable AI solutions.

Team leadership and management

Manage projects: Oversee project planning, resource allocation, and budget management to ensure successful, on-time, and high-quality delivery.
Build and mentor teams: Recruit, develop, and manage high-performing teams of Software/AI/ML engineers, full-stack developers, and MLOps specialists, and beyond.
Foster a culture of innovation while delivering quickly: Encourage experimentation, continuous learning, and adaptability to emerging technologies and trends.

Requirements

Advanced hands-on technical expertise: Demonstrated hands-on expertise in both AI/ML engineering (including LLMs, computer vision, NLP, etc.) and modern full-stack development as an individual contributor.
Experience with cloud and MLOps: Proficiency with cloud environments (AWS, GCP, Azure) and scaling MLOps for model training, deployment, inference, and monitoring.
Leadership experience: Proven track record of leading and managing engineering or AI/ML teams.
Strategic thinking: Ability to develop a long-term technical vision and align it with overall product and business strategy.
Excellent internal and external communication: The ability to communicate complex technical concepts to both technical and non-technical audiences, including executive leadership and Verneek partners.
Startup Experience: Prior track record of having helped built series of technologies at a deeply technical startup.