AI Support Engineer, Biosciences - San Francisco
Posted bythe hiring team· about 3 hours ago
Posted bythe hiring team· about 3 hours ago
AI Support Engineer, Biosciences - San Francisco
USD 180,000 – USD 260,000
Above 84% in Data
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About this role
the company User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. the company customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises.
We are looking for an experienced, hands-on support leader to build and run the support and escalation motion for GPT-Rosalind and the company life sciences customers.
This is both a builder role and a frontline support role. You will work directly with customers, own complex cases, diagnose technical and operational issues, and coordinate cross-functional teams through resolution. You will also create the intake paths, playbooks, knowledge, tooling, and operating mechanisms needed to support life sciences workflows across ChatGPT, Codex, and the the company API.
You’ll partner closely with Account Directors, Product, Engineering and Forward Deployed Engineering, Security, Legal, and bioscience subject-matter experts. You will help customers receive coordinated, accurate answers while maintaining clear boundaries between technical support, scientific consultation, product feedback, and roadmap commitments.
This role is an opportunity to define how the company supports scientists and life sciences organizations as they adopt increasingly capable AI systems.
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 the company 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.
Have 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.
Bring 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.
Have experience supporting enterprise customers through complex technical configuration issues involving access, permissions, environments, APIs, security, or governance.
Demonstrate 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.
Have a 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.
Are 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.
Can balance frequent context switching and broad ownership with careful prioritization, clear communication, and consistent follow-through.
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.
About the company
the company is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
The AI Support Engineer, Biosciences - San Francisco role with the hiring team offers USD 180,000–260,000 per year. Salary information is published as part of every JobRemotely listing so candidates can self-screen before applying.
Yes — the hiring team has marked this AI Support Engineer, Biosciences - San Francisco role as open to candidates based in United States. Eligibility requirements are surfaced in the JobPosting structured data on the listing.
The hiring team uses the JobRemotely structured hiring pipeline: candidates apply through the listing, complete a paid test task or screening, and only then proceed to interviews. This skips the resume black hole and respects everyone's time.
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