Jobs at duvo.ai

Own the technical sales process for enterprise AI workflow automation, including discovery, process mapping, pilot design, demos, technical evaluations, security reviews, integrations, and early platform testing. Partner with Account Executives and customer operations and IT teams, connect solutions to measurable business outcomes, manage scope and feasibility, create reusable sales assets, and transition successful pilots to Forward Deployed Engineering. The role requires hands-on AI knowledge, systems thinking, commercial judgment, and occasional travel.

Lead technical pre-sales activities: run discovery and process mapping, scope pilots, build and demo pilots against customer workflows, own technical evaluations and security/integration questions, guide early testing, manage scope and handoffs to engineering, and create reusable demo assets and playbooks.

Deploy AI agents directly within customer environments by mapping and improving workflows, translating business logic into agent behavior, configuring integrations, writing scripts and prototypes, debugging production systems, and driving measurable customer outcomes. The role combines hands-on AI implementation, process redesign, technical consulting, stakeholder management, and reusable deployment practices. Frequent travel and onsite or hybrid client work are expected.

Own customers’ business transformation roadmaps and measurable outcomes beyond software deployment. Partner with C-level and board stakeholders to build transformation business cases, prioritize processes, lead organizational change, measure ROI, prove results, and drive expansion from pilots to enterprise rollouts. The role requires FMCG or retail expertise, Big Four or top-tier consulting experience, executive credibility, change leadership, and strong outcome measurement skills.

Own the technical story in enterprise deals: run discovery and process mapping, design and build pilots using customers' data and workflows, handle security and integration evaluations, guide early testing, and hand off successful pilots to engineering. Focus on measurable business outcomes and reusable demo assets to accelerate sales.

The Growth Generalist role involves launching products, managing demand generation campaigns, creating content, enabling sales, performing analytics, and filling operational gaps in a startup environment.

The Transformation Manager is responsible for driving business transformation for retail clients by connecting AI capabilities to measurable business outcomes, facilitating change leadership, and ensuring successful adoption of new processes.

The Site Reliability Engineer will manage platform reliability and infrastructure, ensuring security and observability while automating deployments. Responsibilities include incident response, monitoring, and improving reliability practices.

As a Founding Product Manager, you will define product priorities, lead customer discovery, and collaborate cross-functionally to drive successful outcomes in AI operations for retail and CPG enterprises.

The Design Engineer will combine design and engineering skills to create user-facing experiences, working on AI operations platform interfaces and ensuring production-quality outcomes through collaboration and iteration.

The role involves embedding with customers to develop and deploy AI-driven solutions, improving processes, writing integration code, and ensuring successful agent delivery and customer engagement.

The AI Solutions Consultant will design and configure AI agents for retail/e-commerce businesses, identifying automation opportunities and translating business processes into operational solutions. They will collaborate with stakeholders and support sales conversations, ensuring customer satisfaction and effective solution delivery.

The Partner Manager will manage signed partner relationships, coordinate joint selling efforts, onboard partners, track account pipelines, and scale the partner ecosystem to drive revenue and growth.

Build and maintain the data foundation (pipelines, warehouse) and develop AI-native agents and internal workflows on top of it. Enable product and cross-functional teams to make faster, data-driven decisions. Measure success by improving organizational speed and intelligence.