
11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
📱 Media
🤝 B2B
Artificial Intelligence • Media • B2B
Troveo AI is a company that curates, licenses, and delivers large-scale, rights-cleared video datasets engineered for training computer vision and multimodal AI models. They work directly with content creators and global licensors to produce annotated, training-ready clips with custom metadata and legal compliance, serving enterprise AI labs and platforms that need high-quality video for model development (e. g. , avatars, action recognition, and camera-motion-aware models). Troveo operates as a B2B data provider and platform focused on media-originated training data.
🕒 February 26
AWS
Cloud
Distributed Systems
Grafana
JavaScript
Kafka
Kubernetes
Microservices
Node.js
Postgres
Prometheus
Python
SQL
Go
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11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
📱 Media
🤝 B2B
Artificial Intelligence • Media • B2B
Troveo AI is a company that curates, licenses, and delivers large-scale, rights-cleared video datasets engineered for training computer vision and multimodal AI models. They work directly with content creators and global licensors to produce annotated, training-ready clips with custom metadata and legal compliance, serving enterprise AI labs and platforms that need high-quality video for model development (e. g. , avatars, action recognition, and camera-motion-aware models). Troveo operates as a B2B data provider and platform focused on media-originated training data.
• Lead the architecting of Troveo’s data pipelines, systems, and applications for scalability and reliability. • Partner with product, frontend, and DevOps teams to co-design scalable backend architectures. • Architect and deploy microservices in production environments, ensuring orchestration, auto-scaling, and fault tolerance across hybrid or multi-cloud setups. • Build resilient distributed systems addressing challenges like eventual consistency, service mesh (Istio), and event-driven architectures with Kafka or NATS. • Collaborate across teams as a player-coach, mentoring other engineers while delivering hands-on code and system design. • Design and optimize data pipelines that process massive video datasets for AI workloads. • Dive deep into database internals—execution and storage engines, sharding, replication, and vector search techniques—to ensure efficiency at scale. • Extensive experience with AWS, especially S3, for large-scale data processing and storage. • Strong knowledge of SQL (PostgreSQL preferred); Snowflake SQL experience is a plus. • Collaborate with ML and data engineering teams to embed AI/ML models directly into backend services, maintaining contextual awareness of video AI tradeoffs. • Implement comprehensive monitoring, logging, and tracing frameworks (Prometheus, Grafana, Jaeger) to maintain 99.99% uptime. • Build and maintain CI/CD pipelines with GitHub Actions, ArgoCD, or Tekton, integrating security scans and automated testing for zero-downtime deployments. • Profile and optimize backend services for low latency, cost efficiency, and high throughput under load. • Ensure operational excellence under pressure—especially during tight delivery windows—while maintaining clear communication with leadership. • Enforce zero-trust security principles, encryption at rest and in transit, and compliance with GDPR/CCPA. • Work with the platform team to ensure all deployments meet Troveo’s data protection and reliability standards. • Exhibit meticulous attention to detail, ensuring deliverables adhere precisely to contract terms and customer expectations. • Communicate effectively under pressure, providing updates and clarity during time-sensitive project deliveries. • Demonstrate strong lateral and technical communication, sharing customer delivery learnings across the engineering org to strengthen platforms and systems company-wide. • Partner directly with Product to translate requirements into scalable, reliable backend solutions.
• 8+ years of backend software engineering experience, including system architecture and distributed systems design. • Deep expertise in Go, Python, or Node.js, with production microservices experience. • Strong understanding of Kubernetes, container orchestration, and cloud-native architectures. • Hands-on experience with Kafka, NATS, or similar event-driven platforms. • Proven experience operating at scale with a startup mentality - fast-moving, adaptable, and pragmatic. • Familiar with video AI/ML systems - not leading their development, but understanding the tradeoffs that impact system design and performance. • Experience implementing observability and CI/CD pipelines in production. • Excellent communicator and mentor; capable of leading by example and elevating team technical standards.
• Competitive compensation with significant equity upside
Apply Now🕒 February 26
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