Jobs at nexos.ai

Lead end-to-end product analytics: design tracking, build and maintain pipelines and dashboards, ensure data quality, partner with Product and Engineering to deliver actionable insights and instrumentation.

Lead product marketing for an AI no-code platform: develop positioning and narratives, partner with product and GTM teams, translate technical capabilities into customer value, drive launches and enablement for PLG and self-service audiences.

Lead AI/ML innovation and build production-grade, scalable AI systems. Evaluate and integrate LLMs and AI tooling, prototype POCs, contribute across product discovery and delivery, and implement context, retrieval, memory, and agentic solutions.

Lead end-to-end B2B marketing programs for SMB: manage campaigns, events, webinars, calendar, landing pages, and sales enablement. Translate buyer insights into briefs and align cross-functional stakeholders to drive pipeline.

Lead product design for an AI-native SaaS platform: discover problems, run rapid experiments and prototypes, conduct lightweight user research, design trustworthy AI experiences, collaborate with PMs and engineers, and iterate on product systems and patterns while balancing speed and long-term vision.

Build, deploy, and maintain Go-based microservices for an AI platform. Deliver scalable, secure systems, own services end-to-end, collaborate with engineers, and iterate quickly in a startup environment.

Build and improve backend features for an AI orchestration platform. Write scalable, secure, high-performance Go-based microservices, own services end-to-end (implement, deploy, monitor), work with distributed systems and NoSQL, and collaborate closely with other developers in a fast-paced startup environment.

Lead strategy to identify, negotiate, and onboard high-impact technology and system-integrator partners. Manage partner relationships, align initiatives with Product/Sales/Marketing, track partner performance, represent the company at events, and provide partner-driven product feedback to drive growth.

Lead AI technical direction and roadmap; prototype and productionize GenAI systems. Drive research strategy, design evaluation frameworks for LLMs, and build context, retrieval, memory, and agentic features. Work closely with product and cross-functional teams and evangelize AI internally and externally.

Build, own, and maintain Go-based microservices for an AI platform. Implement scalable, secure features for an AI orchestrator, collaborate on system design (DDD), deploy and monitor services, and iterate quickly in a startup environment.

Lead UX for an AI-first SaaS product: discover problems, run rapid experiments and prototypes, validate with user research, design AI-native experiences, and collaborate with PMs and engineers to ship incremental MVPs while maintaining product vision and consistency.

Build, own, and maintain Go-based microservices for an AI orchestration platform. Design scalable, secure systems using distributed technologies and NoSQL, deploy and monitor services (Kubernetes, gRPC, Kafka), and collaborate across teams in a fast-paced startup.

Lead product discovery and design for an AI-first SaaS platform. Run rapid experiments, build prototypes, conduct lightweight user research, design AI-native experiences that manage model limitations, and collaborate with PMs and engineers to iteratively ship coherent, user-focused MVPs while maintaining long-term product vision.

Design, build, and maintain Go-based microservices for a scalable AI platform. Implement performant, secure backend features, own services end-to-end (development, deployment, monitoring), work with distributed systems, NoSQL, and high-load architectures, and collaborate cross-functionally in a fast-paced startup environment.

Build, own, and improve Go-based microservices for an AI platform. Write scalable, secure backend code, design systems using DDD, deploy and monitor services, and collaborate in a fast-paced startup.

Lead go-to-market operations across sales, marketing, and retention. Manage and optimize Salesforce and CRM integrations, maintain accurate CRM data, automate processes, identify operational inefficiencies, and align cross-functional teams to improve reporting and operational effectiveness.