AI Support Engineer, Biosciences

Responsibilities

• Work directly with Rosalind and life sciences customers, taking ownership of complex technical and operational support cases from intake through resolution.
• Diagnose and resolve issues involving onboarding, workspace creation, access and permissions, API and organization configuration, model availability, sandbox or environment setup, and other product configuration questions.
• Support customer workflows across ChatGPT, Codex, and the OpenAI API, including questions about tool access, environment constraints, reproducibility, product behavior, and responsible model usage.
• Build bioscience-aware intake flows, diagnostic procedures, routing logic, escalation paths, playbooks, response templates, and internal and customer-facing knowledge content.
• Determine whether an issue requires technical support, workflow enablement, scientific consultation, solutions architecture, product feedback, or another specialized response, and route it to the appropriate owner without losing context or accountability.
• Coordinate complex escalations across Product, Engineering, Forward Deployed Engineering, Security, Legal, Account Directors, and bioscience subject-matter experts, providing clear handoffs and driving cases through closure.
• Maintain appropriate boundaries around scientific guidance: support standard Rosalind usage and technical workflows while engaging qualified bioscience experts for novel scientific consultation, research optimization, or domain-specific validity judgments.
• Identify recurring issues across scientific workflows, specialized tooling, access and provisioning, governance, and product usage, then turn those patterns into durable fixes, better documentation, and product improvements.
• Build a repeatable customer-feedback loop that captures and synthesizes bugs, product gaps, and unmet needs for the Rosalind, Product, and Engineering teams.
• Use AI, automation, and lightweight technical solutions to improve triage, routing, case summarization, knowledge management, and support quality.
• Help define the long-term operating model, service levels, coverage requirements, and specialization strategy for biosciences support.
• Foster a supportive, rigorous, and customer-focused culture within User Operations.

Requirements

• 8+ years of experience in technical support, support engineering, escalations, technical account management, solutions operations, product operations, incident management, or a related customer-facing technical role.
• Meaningful familiarity with life sciences disciplines or workflows, such as computational biology, bioinformatics, genomics, transcriptomics, drug discovery, or related fields.
• Can rapidly understand and triage questions involving scientific tools and workflows while recognizing when specialized scientific expertise is required.
• Experience supporting enterprise customers through complex technical configuration issues involving access, permissions, environments, APIs, security, or governance.
• Strong technical troubleshooting and root-cause analysis skills, including the ability to investigate novel or poorly defined problems.
• Communicate clearly and credibly with scientists, platform administrators, engineers, Product teams, Security, Legal, and go-to-market partners.
• Track record of building playbooks, intake systems, escalation paths, knowledge programs, reporting, or other foundations for a new or rapidly scaling support function.
• Exercise sound judgment when distinguishing among break-fix support, workflow enablement, scientific consultation, product feedback, and roadmap requests.
• Thrive in ambiguity, create structure where processes and ownership are still emerging, and remain effective while priorities evolve.
• Build strong relationships with customers and cross-functional partners and can lead complicated issues to resolution without relying solely on formal authority.
• Comfortable using tools such as ChatGPT, Codex, APIs, scripting, or automation to improve repetitive operational work.
• Approach unfamiliar problems with humility, curiosity, and a willingness to learn whatever is needed to help customers and teammates succeed.
• Balance frequent context switching and broad ownership with careful prioritization, clear communication, and consistent follow-through.

Nice-to-Haves

• Experience supporting software, data, or AI products used in regulated or security-sensitive scientific environments.
• Experience working with computational research environments, scientific software, cloud platforms, APIs, or data-intensive workflows.
• A degree or equivalent practical experience in a life sciences, computational, engineering, or other relevant technical field.