You will work directly with enterprise customers to design, build, and deploy agentic AI solutions that address their specific business needs. This involves managing the end-to-end technical deployment process and presenting working prototypes to both technical and executive stakeholders.
You will lead the technical customer journey for enterprise accounts by designing scalable AI-powered solution architectures and managing the full lifecycle from discovery to deployment. Additionally, you will act as a technical leader to define internal playbooks, mentor the solutions team, and bridge the gap between customer needs and product development.
Develop agent memory systems and mechanisms for reasoning, curation, and storage without model retraining. Design reusable agent skills and establish benchmarks to evaluate and improve agent behavior at scale.
Own the end-to-end backend architecture, data layer, and API design for a new greenfield customer-facing product. Contribute to the frontend as needed to ship features across the entire stack within an AI-driven workflow.
Own the end-to-end frontend architecture and UI design for a new greenfield product. Contribute to backend development and system design while utilizing AI-driven workflows to ship features.
The role involves working directly with enterprise customers to design, build, and deploy agentic AI solutions and prototypes. You will own the end-to-end technical path to value, from initial evaluation and solution design to production go-live.
Architect and build a distributed backend for agent orchestration and workflow execution using Temporal and sandboxed environments. Own the distributed data pipelines and event-driven infrastructure to ensure platform resilience and scalability.
Design and build AI-driven agentic systems and knowledge graphs to detect policy violations and compliance risks within organizational data. Lead the technical approach for the Org Intelligence team, owning the development process from architecture to production delivery.
Drive the go-to-market strategy by translating complex AI capabilities into differentiated narratives for enterprise buyers. Lead end-to-end product launches and partner with sales teams to create enablement assets and drive pipeline impact.
Establish and lead the SRE function by defining reliability standards, architecting scalable production environments, and embedding operational excellence across engineering. The role involves managing the SRE team and reporting to the CPTO to ensure the stability of AI products.
Design and implement scalable automated testing solutions focusing on API and UI automation for AI-based systems. Collaborate with engineering teams to define QA processes, improve CI/CD pipelines, and ensure high test coverage.
Design and build scalable search and retrieval systems and data pipelines to power AI agents. Own the end-to-end development of the context management layer, integrating diverse enterprise data sources and optimizing for latency and relevance.
Act as the primary relationship owner for enterprise customers to drive adoption, measurable business value, and long-term account growth. Coordinate cross-functionally with technical and sales teams to ensure customers operationalize and expand their use of the AI infrastructure.
Architect and operate scalable, secure production environments while leading reliability improvements across multiple engineering streams. Focus on evolving Kubernetes-based infrastructure, optimizing CI/CD pipelines, and productionizing ML workloads.
Design and implement AI-driven workflows and agentic solutions to solve complex business problems for enterprise customers. Lead technical validation pilots and partner with sales and customer success teams to drive platform adoption and expansion.
Lead enterprise sales efforts in Israel and the Middle East, focusing on high-value deals with banks, insurance companies, and government entities. Own the full sales lifecycle from executive outreach to closing, while positioning Wand as a strategic AI transformation partner.
Lead technical pre-sales engagements by architecting high-impact AI solutions and designing prototypes to prove business value. Build the foundation for the customer engineering function by developing reusable demo systems, playbooks, and mentoring a high-performing SE team.
