Brainbox Consulting BV aligning great talent with clients’ needs is at the core of who we are. We are passionate about our Consultants, our Clients, and our Partners. Our rich IT legacy combined with our unyielding care for our people and business is the driving force behind all we do, and we deliver! On this journey, we are looking for Lead AI Engineer who is also interested to take on a wide range of activities.
The AI Lead Engineer in the Data Analytics team is responsible for leading the design, development, and maintenance of scalable and robust AI platform and AI solutions. You will play a pivotal role in operationalizing AI/ML workflows, optimizing infrastructure, and enabling efficient, secure, and reliable AI deployments. This role is crucial for maintaining high availability, scalability, and performance of AI services while collaborating with global teams to ensure cohesive strategy and implementation.
Role and responsibilities
- Mentor engineers across multiple AI focused teams, lead the design, development, and maintainability through CI/CD of scalable AI/ML workloads across hybrid cloud environments
- Design and implement API’s to securely expose platform services (ex. AI models) and to integrate loosely coupled application components
- Automate infrastructure provisioning using Infrastructure-as-Code (IaC) tools like Terraform or Ansible. Implement testing of automated deployments and observability frameworks (ex. Prometheus, Grafana, or Datadog) for application functionality including monitoring, logging, and tracing
- Coach colleagues in developing solutions in line with industry best practices and ‘socialize’ generalized frameworks to standardize development. Responsible for quality reviews, guiding cross sector co-development initiatives and continuous improvement.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 8+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering, with a focus on AI/ML.
- Strong expertise in cloud platforms (Azure, Google Cloud, or AWS) and Kubernetes (both SDLC on Kubernetes and Kubernetes core underlying components)
- Experience with GPU-accelerated compute environments and AI-specific tools like NVIDIA Triton, Kubeflow, or MLflow.
- Strong software engineering expertise in MLOps practices and proficiency in scripting (Python, JavaScript, Bash, or equivalent).
- Strong hands-on experience with Infrastructure-as-Code (IaC) frameworks like Terraform
Job Features
Position | Lead AI Engineer |
Work location | Veldhoven |
Experience | 8+ yrs |
Education | Bachelor or Master's |
Required Skills | DevOps, Kubernetes, Terraform, Azure, Google Cloud |