Vectara
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Recently posted jobs
Machine Learning • Software
Own and improve infrastructure for a deploy-anywhere AI platform across AWS, GCP, and on-premises environments. Build Terraform and Helm infrastructure, manage Kubernetes clusters, CI/CD pipelines, GitOps workflows, observability, and ML inference workloads. Contribute to backend services in Java and Python, support enterprise deployments, improve reliability and scalability, and participate in on-call operations.
Machine Learning • Software
Serve as the technical sales and customer-facing expert for an AI platform. Responsibilities include conducting product demonstrations, supporting proofs of concept, advising on architecture and development, planning professional services projects, tuning retrieval and agentic pipelines, responding to RFPs, supporting customer adoption, and communicating product feedback internally. The role requires strong AI, cloud, on-premise, application development, storytelling, and enterprise customer engagement experience.
Machine Learning • Software
Lead product strategy and execution for Vectara’s enterprise AI platform. Own the roadmap, customer discovery, competitive intelligence, packaging, pricing, product definition, and market positioning. Coordinate Product, Engineering, ML, Sales, Marketing, and Field Engineering to deliver successful launches and customer outcomes. Represent the company in customer meetings, analyst relations, and field marketing events while translating market needs into differentiated product initiatives.
Machine Learning • Software
The Account Executive will manage sales cycles for SMB customers, generating leads, guiding prospects, and articulating Vectara's AI technology value while ensuring customer satisfaction and consistent quota attainment.
Machine Learning • Software
Lead development of scalable backend services and platform infrastructure for an AI agent platform. Responsibilities include architecture and code reviews, infrastructure automation, CI/CD, observability, reliability, distributed systems, ML/NLP workload support, and mentoring engineers. The role requires expertise in Java, Python, cloud environments, Docker, Kubernetes, infrastructure-as-code, monitoring tools, and data infrastructure.
