Ai Solutions Specialist

iBET is seeking a highly motivated AI Solutions Specialist to help embed generative AI across its research areas and satellite labs.
The AI Solutions Specialist will report directly to the CTOO and play a crucial role in turning iBET's Digital Transformation Programme from an exploratory initiative into an institution-wide capability. This role encompasses a diverse set of responsibilities, including hands-on coaching of scientific champions, support for iBET's internal AI server, training delivery and workflow implementation.
As AI Solutions Specialist, you will make AI adoption real for iBET's researchers and satellite labs, supporting world-class research and development. You'll work hands-on with scientific champions across very different research areas, help operate iBET's internal AI server, and turn working prototypes into properly governed, adopted workflows.
Champion enablement across scientific domains
Work directly and primarily with Research champions – each expert in a different scientific area – running working sessions.
Provide first-line troubleshooting so champions are not blocked between coaching sessions.
Extend the same support to Operations and Administration & BD champions as capacity allows.
Follow up on stalled or pending-review initiatives and help move them toward sign-off.
Internal AI server & open-source model support
Support the rollout of Gen AI solutions on iBET's internal AI server, working alongside IT on the application/model side of existing and future agents.
Work comfortably in a Linux environment and with open-source, self-hosted large language models — configuring, testing and troubleshooting models or agents on the internal server.
Act as the day-to-day link between Research and IT.
Training delivery
Deliver baseline AI-fluency sessions (prompt literacy, tool awareness) as the programme extends across iBET.
Deliver workflow-specific upskilling to champions and first-wave users, tailored to each scientific area or function.
Build and maintain a lightweight training curriculum and materials library.
Gen AI workflow implementation acceleration
Support scheduling and preparation of Gen AI based workflows workshops, gathering context from champions beforehand.
Help champions design and run pilot stages for their workflow: shadow-mode setup, pass/fail criteria and usage tracking.
Assist in producing and filing documentation alongside the relevant champion.
Tracking, measurement & reporting
Own day-to-day maintenance of the AI Initiatives Tracker — status, champion, stage and next steps kept current.
Support champions in setting baselines and tracking AI health indicators (override rate, escalation rate, adoption/usage rate).
Prepare periodic progress rollups for the CTOO and Executive Commission.
Governance support
Reinforce data-classification practice when onboarding champions, including Restricted-data handling and data-owner approval.
Flag adoption or governance risks early, rather than letting them surface only at a formal review.
Scientific background in life sciences, biotech, or a related field (or equivalent hands-on research experience), with a demonstrated ability to quickly learn an unfamiliar scientific domain well enough to work productively with the expert who owns it.
Comfortable working in a Linux environment and with open-source, self-hosted large language models (e.g. llama, QWEN, Mistral or similar).
Genuine, hands-on comfort with generative AI tools (Claude and/or Copilot) — able to demonstrate use, not just describe it.
Strong facilitation skills: comfortable coaching researchers one-on-one and translating a tool's capability into what it means for their specific workflow.
Organised enough to own a lightweight tracking system across many small, concurrent initiatives without imposing heavy process on champions.
Fluent in Portuguese and English.
Nice to have: background in training/L&D or change management; familiarity with data-governance concepts (data classification, GDPR); instructional design experience.
Opportunity to help shape a flagship AI Digital Transformation programme from an early stage.
12-month fixed-term contract, full-time, renewable subject to programme continuation.
Direct collaboration with the CTOO and scientific leadership across iBET's research areas and satellite labs.
Professional development and growth opportunities in a cutting-edge biotech R&D environment.
Collaborative and innovative workplace culture.
Applications will be evaluated based on CV merits, motivation, and experience according to the profile described in this announcement.
Does this sound like the right challenge for you?
#J-*-Ljbffr