• Define and prioritize the product roadmap for AI-driven solutions applied to the healthcare sector, aligning with FinX's strategic objectives. • Translate business, regulatory, and clinical requirements into technical specifications and clear user stories for engineering and data teams. • Collaborate with Data Science/ML teams to assess feasibility, performance, and risks of AI models applied to the product. • Conduct market and user research (healthcare professionals, patients, health plan operators) to validate product hypotheses. • Define success metrics, monitor KPIs, and run experiments (A/B tests) to inform product decisions. • Ensure compliance with healthcare regulations and best practices (data privacy, LGPD, information security) in solution development. • Act as a bridge between business stakeholders, technology teams, and regulatory/compliance areas.

• Manage the execution of go-to-market projects, campaigns, and product launches • Coordinate with Product, Sales, Design, and other teams to ensure timely and effective deliverables • Partner with Demand Generation and Corporate Marketing on campaign execution and content support • Support Voice of Customer programs, including administration of customer feedback platforms (e.g., G2) and helping translate insights into messaging • Create and edit Google slides and supporting materials for executive and customer-facing use • Support competitive analysis and content rollout • Organize and run meetings with internal stakeholders and track action items • Conduct research (e.g., Gartner, market/competitive analysis) to inform positioning • Contribute to messaging, positioning, and enablement initiatives • Help build scalable processes for launch planning and cross-functional collaboration

• Own the gateway-to-processor certification pipeline end to end, maintaining a single, current source of truth for every open and upcoming certification across processors and acquirers, including status, owner, target dates, and outstanding test cases. • Take ownership of processor and acquirer certification relationships, acting as the primary point of contact and building the working rapport that gets NMI prioritised when certification queues are long. • Negotiate test scope with processors, scoping certification suites down to what is genuinely required, challenging redundant or non-applicable cases, and reducing certification burden without compromising correctness or compliance. • Proactively identify certification blockers and schedule risk, driving each open certification to completion as quickly as the external party will allow. • Escalate and clear third party blockers, chasing responses, escalating through the right channels, and removing dependencies before they become delivery risk. • Clearly articulate certification status, timelines, and trade-offs to engineering, product, and enterprise sales stakeholders, so certification timing feeds directly into deal and delivery planning. • Partner closely with the Protocols engineering team to sequence certification against development, surface issues early, and ensure test failures are triaged and resolved quickly. • Drive improvements in how certification is tracked, forecast, and reported, raising the visibility and predictability of the pipeline over time. • Ensure certification work adheres to the relevant card network rules and compliance standards (e.g., PCI, card scheme mandates) throughout. • Contribute to preventative improvements, capturing lessons from stalled or delayed certifications and feeding them back into how the team plans future work.

Role Description The Associate Product Enablement Specialist, AI will serve as an associate professional supporting the enablement of AI-powered platform capabilities across the company ecosystem, under the guidance of senior team members. The role contributes to the implementation, testing, evaluation, and operational readiness of AI agents and AI-assisted workflows, with an initial focus on the evaluation pipelines and observability tooling used to measure their quality, reliability, and cost. Measurement is the foundation of enablement, and this role helps build and operate it. The role will assist with AI capability implementations, support evaluation and testing activities, contribute to documentation efforts, and provide first-line support to internal teams adopting AI capabilities. This individual contributor role offers structured learning opportunities and mentorship while building foundational skills in AI product enablement. Qualifications - 0-2 years of professional related experience - Academic, internship, or project experience in software development or technical support - Basic understanding of software applications and how they are built - Strong learning aptitude - Professional communication skills - Working proficiency in Python and/or TypeScript a plus - Comfort with the command line, git, and following technical instructions - Basic understanding of containers (Docker or similar) - Curiosity about LLM-based systems and AI agents, including how tool calling, prompts, and pipelines work - Comfort with learning new technologies - Strong written communication skills - Detail-oriented, evidence-first approach - Ability to explain technical concepts in practical terms - Time management skills and follow-through on tasks - Team player mindset - Eagerness to learn - Adaptability - Professional demeanor - Organizational skills - Receptive to feedback Requirements - Assist senior specialists with implementing AI agents and AI-assisted features in product workflows - Support configuration of AI pipelines and execution environments - Help with system setup tasks across product environments, local and cloud - Document implementation and integration steps as runbooks - Author evaluation tasks under guidance and run evaluation pipelines for AI outputs - Execute functional, reliability, and performance test runs of AI agents across models - Record and report evaluation results, including scores, cost, and latency - Assist with human-in-the-loop validation - Help operate the observability tooling used to monitor AI agents, pipelines, and workflows - Investigate traces of AI agent activity - Respond to basic inquiries from internal teams - Track and document operational issues - Compile usage, cost, and reliability reports - Contribute to documentation projects - Update existing materials and review documentation for accuracy - Create simple user guides for internal tools and workflows - Support training sessions and onboarding of teams adopting AI capabilities - Complete product and domain training programs - Shadow senior team members on implementations - Participate in customer and internal-stakeholder calls as an observer - Practice with the AI platform, evaluation harness, and observability stack - Participate in team meetings and contribute to team discussions - Assist colleagues across product teams with enablement tasks - Share observations on usability and adoption challenges - Support process improvements and maintain team documentation Benefits - Fully remote work - Flexible schedules - Generous vacation policy - Affordable health coverage - Annual bonus Education - Bachelor’s degree in computer science, data science, artificial intelligence, life sciences, or related field - Masters or PhD in computer science, data science, artificial intelligence, life sciences, or related field preferred