AI Platform Engineer
Role details
Job location
Tech stack
Job description
As an AI Platform Engineer, you'll shape the technical backbone of our platform, collaborating with the founding team to build reliable and scalable AI systems.
You will:
· Design infrastructure to support high-performance ML model deployment and real-time inference
· Build scalable APIs and microservices for AI and data integrations
· Develop CI/CD pipelines and containerized environments (Docker, Kubernetes)
· Implement observability, monitoring, and alerting across the platform
· Collaborate cross-functionally with ML engineers and product teams
· Contribute to architectural decisions and influence engineering culture
How you will make 10X Impact by:
· Building infrastructure that makes real-time ML performance seamless
· Enabling rapid experimentation, testing, and deployment of models
· Establishing best-in-class engineering standards and systems reliability
· Influencing core architecture and platform strategy from day one
As an early team member, you'll have a unique opportunity to shape our technical direction and growth. Some travel may be required as we build our distributed team.
Requirements
· 6+ years in backend/platform/infra engineering; 2+ years in ML/AI systems
· Strong systems design and implementation experience with microservices architectures, API and agentic model protocol design
· Proficiency in Python; exposure to Go/Rust/Java for performance-critical code
· Expertise in Docker, Kubernetes, Terraform, and cloud-native infrastructure (GCP/AWS)
· Track record of designing and implementing production-grade infrastructure and DevOps practices including enterprise grade CI/CD, infrastructure as code, and automated testing
· Experience with CI/CD pipelines, microservices, and secure network architectures
· Real-time systems (Kafka, Redis, Pub/Sub) and observability stacks (Prometheus, Grafana, etc.)
· Ability to discuss and debate relative merits and opportunities in technical decision making
Extra bonus:
· Exposure to ML model serving, feature stores, or vector databases
· Fintech, gaming, or real-time decisioning systems background
· Startup or consulting experience
Competencies / behaviours
- Integrity and ownership mindset
- Curious and driven to learn fast
- Team player who thrives in ambiguity
- Passion for building things that matter
- Fast and keen learner