Jobs at Orbital

Design and implement scalable backend systems and AI-driven workflows, optimize for performance and availability, integrate cloud services and databases, collaborate with product and customers, write maintainable code, and mentor junior engineers.

Lead architecture, implementation, and optimization of scalable backend systems and AI-driven workflows. Integrate LLMs, agentic frameworks, and automation to enhance sales intelligence. Drive features from design through deployment, ensure high availability and low latency, write maintainable code, and champion engineering best practices.

Own and scale large data ingestion and enrichment pipelines using SQL and Python. Build AI-powered systems with LLMs, embeddings, and vector search for extraction, classification, and entity resolution. Design data models, maintain warehouse/CRM sync, ensure data quality, and optimize AI infrastructure for cost and performance while mentoring teammates.

Own and prioritize the data platform roadmap (ingestion, enrichment, matching, vertical models, warehouse/CRM sync). Turn ambiguous data problems into buildable specs, manage data quality feedback loops, evaluate third-party data vendors, control enrichment/AI costs, and partner with engineering, design, and GTM to ship high-impact data features.

Own onboarding and ongoing success for large US customers: teach platform use, build and tune no-code AI agent workflows, advise strategically, monitor health signals, resolve issues, and drive retention and expansion.

As a Customer Success Engineer, you will manage customer support, troubleshoot product issues, follow up on tickets, and collaborate with engineering teams.