About Pinyahta Pinyahta is building a trust-first SaaS platform for senior revenue leaders navigating high-risk roles across marketing, sales, customer success, and operations. Revenue team failure is systemic, predictable, and largely invisible before leaders take the job. Roles don’t usually break all at once—they erode through misalignment of expectations, authority, investment, and influence. Pinyahta exists to surface that signal early, before leaders step into environments that are structurally set up to fail. Marketing leaders are our initial go-to-market entry point , providing a focused wedge to validate the platform before expanding to additional revenue-critical functions over time. This is not a growth-at-all-costs product. It is a credibility-driven platform designed to make revenue reality visible—and help leaders and companies make better decisions. The Role Pinyahta is seeking a Founding CTO to act as the technical co-builder and long-term steward of the platform. This is an equity-only role at the earliest stage , designed for someone who genuinely believes in the problem Pinyahta is solving and wants to help define what the market will need—not just what it asks for today. You will own technical architecture, foundational product execution, and early technical judgment, while partnering closely with the founder on product direction, sequencing, and tradeoffs. This is not a consulting role. This is not an advisory title. This is a true founding partnership in practice. Time Commitment Approximately 5–7 hours per week in the earliest phase Work is milestone-driven rather than time-based Commitment is expected to increase as the platform approaches launch, traction, and funding milestones Clear path to a higher-commitment or full-time CTO role post-funding or revenue What You’ll Own Technical Foundation Define and evolve the platform’s technical architecture Make pragmatic decisions around stack, infrastructure, and data models Balance speed with long-term maintainability, trust, and scalability Technical Approach (Early Stage) Pinyahta’s MVP is being built using Bubble as a deliberate choice to move quickly, validate signal, and remain capital-efficient at the earliest stage. The Founding CTO will be responsible for evaluating, evolving, and extending this architecture over time—ensuring the platform remains secure, scalable, and credible as usage, data volume, and product complexity grow. This role is not about being “pro” or “anti” any specific tool. It is about making sound technical decisions at each stage and knowing when abstraction is an advantage—and when deeper investment is required. Product Execution Build and ship core platform features incrementally Own reliability, performance, and data integrity Create clean, extensible foundations without premature over-engineering Trust, Privacy & Signal Design systems that protect user privacy and platform credibility Build guardrails that surface signal while preventing misuse or gaming Establish security and access standards appropriate for a trust-based platform Market-Aware Thinking Anticipate what senior revenue leaders will need months ahead of demand Challenge roadmap assumptions when market signals suggest a better path Help Pinyahta stay ahead of the curve as the category takes shape Founder Partnership Act as a thought partner on feasibility, sequencing, and constraints Translate product intent into thoughtful technical solutions Bring independent judgment—not just execution What You’ll Build (Early Focus) User authentication and role-based access Structured assessments and scoring logic Company- and role-level data models Visibility controls, moderation logic, and guardrails Admin tools for platform oversight Scalable foundations for future features as the product matures What Will Set You Apart You genuinely care about the problem Pinyahta exists to solve You’ve personally experienced misalignment, underinvestment, or accountability gaps in senior roles You see technology as a way to surface truth—not just ship features You enjoy thinking ahead of the market and shaping what comes next What This Is Not Not a resume-driven CTO role Not a fractional or advisory engagement Not a large-team management position (yet) Not a place for hype-led or ego-driven architecture Compensation & Stage Equity-only, founding-stage structure Meaningful ownership aligned with long-term impact Pinyahta is pre-launch, building toward a 2026 market debut, and selectively raising a pre-seed round to accelerate expansion and early go-to-market momentum Clear path to a compensated executive role as funding and revenue milestones are reached Why Join Pinyahta Build something principled, needed, and durable Shape a platform that improves how revenue leaders choose and experience work Partner with a founder who values clarity, judgment, and respect Help define a new category before the market fully names it

• Lead the development of machine learning models and data-driven algorithms for high impact projects • Collaborate with product and platform teams to own ML solutions end-to-end • Understand the runtime complexity of algorithms and the cost to run ML models at a production scale • Clearly communicate modeling decisions, tradeoffs, and limitations to technical and non-technical stakeholders • Build, deliver, and maintain enterprise products, ensuring they meet high-quality standards while shipping fast • Take ownership of your work, from design to implementation and maintenance, and drive projects to successful completion • Support production systems, handling debugging challenges in distributed systems to ensure reliability and uptime • Adapt quickly, bringing in latest developments in AI and machine learning, and proactively apply this knowledge to drive innovation within the company

• Develop and Optimize Computer Vision Algorithms • Contribute to BEV and 3D Perception Architectures • Data Management and Processing • Model Deployment and Optimization • Cross-functional Collaboration • Research and Innovation • Leadership

Role Description As a Senior Machine Learning Engineer at FreshBooks, you will own the full machine learning lifecycle, from early experimentation and prototyping to deployment and monitoring in production. You will work on moderately complex problems, refine ML processes, and support teammates through mentorship and collaboration. You will help deliver ML-powered features while optimizing systems for reliability, performance, and rapid experimentation. This role is primarily focused on machine learning, with supporting software engineering skills to enable production deployment. This role is ideal for someone who enjoys taking ideas from concept to customer impact. NOTE: This role can be worked remotely from the above location. What You’ll Do - Design, prototype, and validate machine learning models for product features and internal tools - Own the ML lifecycle from experimentation through production deployment and monitoring - Partner with Data Engineering and Product Engineering to integrate models into batch and online systems - Build and maintain shared feature pipelines, including documentation and versioning - Write production-ready code with testing, observability, and monitoring - Design experiments (A/B test, pre/post analysis) and interpret results to guide product and business decisions - Improve ML reliability through retraining workflows, drift detection, and root cause analysis - Design and build end-to-end pipelines for classification, ranking, embeddings, or generation tasks Qualifications - 5+ years of experience in data science, applied ML, or ML engineering roles - Strong foundation in supervised and unsupervised learning, statistical modeling, and experimentation techniques - Experience developing and shipping ML models in production (batch or real-time) - Strong Python and SQL skills with experience working with structured and unstructured data - Hands-on experience building and deploying ML or LLM-based systems (e.g. retrieval-augmented generation, embeddings, prompt tuning) - Familiarity with cloud infrastructure and ML tools, ideally on Google Cloud Platform (e.g. Vertex AI, BigQuery, Cloud Composer, Kubernetes) - Experience working with CI/CD pipelines, containerization (Docker), and job orchestration tools (Airflow, dbt, etc.) - Strong communication skills and ability to explain technical concepts to non-technical stakeholders You’ll Stand Out If You Have - Experience working with agentic models - Familiarity with LLM orchestration frameworks (e.g., ADK, LangChain, Semantic Kernel, Haystack) - A background in software engineering (e.g., system design, APIs, or distributed systems)