AI Forward Deployment Engineer

Company Description Vokram is an applied deeptech AI lab focused on multi-agent safety, security and governance, working at the intersection of advanced AI research and real-world deployment. The organization is currently operating in soft stealth, offering team members the opportunity to shape early-stage technology and infrastructure. Team members collaborate closely across disciplines to design, test, and refine multi-agent architectures that can be reliably deployed in complex environments involving heavy compliance and critical decision making.Role Description The AI Forward Deployment Engineer is a full-time, on-site role based in Berkeley, CA. This is a customer-facing technical position: the engineer is expected to interact with customers directly, on-site and remotely, serving as the technical bridge between our research and engineering teams and the people deploying our systems in the field. We highly value clear and precise communication, and we are looking for highly motivated, autonomous people who thrive in a fast-paced startup environment. We believe that we are working on one of the most important problems of this decade and would like to work with equally hardworking people who believe AI safety & security This role also focuses on deploying, configuring, and maintaining AI systems in production-like environments, working closely with external engineering teams to translate prototypes into resilient, operational solutions. Day-to-day responsibilities include diagnosing and resolving technical issues alongside customers, integrating AI components with existing infrastructure, and ensuring systems meet safety, compliance, and performance requirements. The engineer will collaborate directly with customers and internal stakeholders to understand deployment needs, create documentation and runbooks, and implement monitoring and incident response procedures. The role also involves iterating on deployment pipelines, improving reliability and scalability, and relaying customer feedback to development teams to enhance system design and multi-agent behavior. There is also opportunity to further develop product features for specific customers.Because this role sits at the interface between customers and our internal teams, strong communication is essential at every scale: from precise, low-level technical discussions with customer engineers, to clear status updates and incident communications, to high-level briefings for non-technical decision-makers and executives. QualificationsExcellent written and verbal communication skills, with demonstrated ability to communicate clearly and precisely across all levels with the ability to explain deep technical details to engineers, writing crisp documentation and incident reports, and while also being able to present to non-technical customer stakeholders and leadership.Comfort and professionalism in direct customer interaction, including on-site engagements, requirements gathering, live troubleshooting sessions, and managing expectations under pressure.Strong troubleshooting and technical support skills to diagnose, analyze, and resolve complex system issues in live or test environments.Networking and integration skills to connect AI services with APIs, data sources, and infrastructure components securely and reliably.Solid operating systems knowledge (e.g., Linux-based environments) to manage system configuration, performance, and automation.Experience with deploying machine learning or AI systems in production, including containerization, orchestration, or similar tooling.High degree of motivation and autonomy; comfort working in a high-ambiguity, early-stage, fast-paced startup environment, with the ability to collaborate cross-functionally and communicate clearly with technical and non-technical stakeholders.Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience in forward deployment, site reliability, or systems engineering.A deep interest in and understanding of AI safety and security, and a conviction that building safe, secure AI systems is one of the most important problems of the next decade.