Generative AI Engineer

GenAI Developer – Reliability Engineering About the Opportunity We’re seeking a GenAI Developer to join a team focused on improving the reliability and efficiency of large-scale direct-to-consumer platforms. This role involves building and applying AI-driven solutions to reduce operational friction, predict and prevent issues, and enhance engineering workflows, specifically within the OTT/streaming domain. The Role As a GenAI Developer, you’ll design and implement AI-powered tools and models tailored to the challenges of high-scale streaming services. This includes leveraging machine learning, natural language processing, and automation to improve observability, detect anomalies, streamline operations, and ensure seamless video delivery. Key Responsibilities • Develop and deploy GenAI solutions to improve reliability, performance, and user experience in OTT environments. • Apply ML/NLP models for anomaly detection, root-cause analysis, and predictive issue resolution. • Build tools that integrate with streaming observability, incident management, and performance monitoring systems. • Partner with reliability engineers, SREs, and product teams to identify high-impact OTT use cases for AI. • Continuously refine AI models to adapt to evolving streaming workflows and scale requirements. • Contribute to building a long-term AI/automation strategy for reliability in video delivery. What You’ll Need • Proven experience in the OTT/streaming video industry (DTC, broadcast, or content delivery). • Strong programming skills (Python preferred) with hands-on experience in ML/AI frameworks. • Demonstrated ability to build and deploy GenAI or ML models in production. • Knowledge of streaming reliability challenges (QoE, buffering, latency, error recovery). • Understanding of observability and reliability practices: monitoring, alerting, incident response, and automation. • Excellent collaboration and communication skills, with experience working in distributed teams. Nice to Have • Experience applying AI/ML to large-scale video platforms or distributed systems. • Familiarity with streaming observability tooling (e.g., Conviva, Datadog, Grafana, Prometheus). • Background in DevOps, SRE, or performance/reliability engineering for OTT. • Experience fine-tuning LLMs or applying prompt engineering for operational automation.