• Co-facilitate diagnostic workshops (Mini-H) with prospective clients alongside the CEO: map processes, build impact baselines, produce AS-IS and TO-BE flow diagrams. • Lead the AS-IS process mapping block of each workshop — steps, owners, systems, handoffs, failure points. • Build the business case (baseline + TO-BE agentized) that underpins every VAP proposal. • Qualify leads between the initial meeting and the workshop: confirm problem, interlocutor authority, and willingness to act. • Run the Hypothesis phase of each VAP: map financial and operational opportunity drivers, score by impact × feasibility × speed, select the first deployment target. • Document client processes with engineering-level precision: inputs, outputs, owners, systems, data flows, exception handling. • Design the AI agent blueprint for each VAP: what the agent does, what data it needs, how it integrates, what the human touchpoints are. • Manage delivery cadence: daily standups, weekly deep-dives, biweekly steering sessions. • Build and maintain standard templates for Mini-H facilitation, AS-IS mapping, and VAP scoping.

Role Description We’re looking for an exceptional early-career engineer who has grown up building with AI. You may be fresh out of university, still studying, or entirely self-taught. What matters most is raw ability, curiosity, strong technical instincts, and a genuine obsession with modern AI tooling. This is a high-growth role for someone who wants to learn how a company is built from the inside while contributing to real product work from day one. You’ll work closely with the founders and senior engineers, build real features and prototypes, and learn how to use AI agents to move faster than traditional teams. What You’ll Do - Build real features, prototypes, and demos using tools like Codex, Claude Code, and modern AI coding agents. - Turn ideas into working demos quickly, then help make them more reliable, scalable, and production-ready. - Learn how to direct, evaluate, and control AI coding agents to multiply engineering output. - Work closely with founders and senior engineers across product, engineering, and strategy. - Explore new AI development workflows and help the team move faster. - Contribute to a fast-moving product where experimentation, speed, and quality all matter. Qualifications - You build with AI tools regularly and can show us what you’ve made. - You have examples of projects, repos, demos, prototypes, or technical experiments. - You’re excited about tools like Codex, Claude Code, Cursor, AI agents, and agentic development workflows. - You learn by building and ship constantly. - You have strong technical curiosity and are willing to figure things out independently. - You care more about output and learning speed than titles or credentials. - You’re comfortable working in a fast-moving environment with real responsibility. Bonus Points - You’ve created content, demos, or tutorials around AI or software development. - You’ve tried to start something of your own. - You have a side project you’re deeply interested in. - You’ve experimented with AI agents, coding workflows, automations, or developer tools. - You’re interested in AI infrastructure, enterprise AI, governance, or agentic systems. Benefits - Front-row seat: Learn how a company is built directly from founders and senior engineers. - Real responsibility: You’ll work on meaningful projects, not just small tasks. - Strong mentorship: You’ll be supported while being pushed to grow quickly. - Frontier work: Build in one of the most exciting categories in tech right now. - Output-first culture: We care about what you can build, learn, and ship. What We Offer - Work alongside the ChainGPT core team on high-impact AI and Web3 products across our ecosystem. - Remote-first setup with flexible hours, focused on outcomes, trust, and ownership. - Competitive compensation, with performance-based upside where applicable to the role. - Fast-moving environment with direct collaboration across all team members, including senior management, and clear accountability with no micromanagement. - The support to do your best work, including the tools you need, structured onboarding, and clear room to grow.

Role Description You'll work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack. This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure. Responsibilities - Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml - Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments - Integrate AI features into existing products, enriching them with the latest advancements in machine learning - Excellent programming skills in C++, experience in Javascript is a bonus - Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures - Good understanding of deep learning concepts and model architectures - Experience with transformers, LLMs, Diffusion models - Demonstrated ability to rapidly assimilate new technologies and techniques - A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D Benefits - Remote flexibility: Work where and how you work best - we trust you to deliver - Fair compensation: Competitive salary + benefits that matter (medical, learning) - Ownership opportunities: See a problem worth solving? Own it. We back smart risks over bureaucratic safety - AI enhancement: We leverage AI to make you faster and stronger - complementing your abilities, not replacing them - Learning investment: English classes, professional development - Career progression: Real paths up, not just sideways shuffling - Responsive teammates: No ignored Slacks, no "not my problem" attitudes - Supportive culture: When you're stuck, people help. When things break, we fix them together - Human connections: Regular meetups, tech talks, and actual relationships beyond work

Role Description You'll work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack. This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure. Responsibilities - Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml - Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments - Integrate AI features into existing products, enriching them with the latest advancements in machine learning - Excellent programming skills in C++, experience in Javascript is a bonus - Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures - Good understanding of deep learning concepts and model architectures - Experience with transformers, LLMs, Diffusion models - Demonstrated ability to rapidly assimilate new technologies and techniques - A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D Qualifications - Excellent programming skills in C++ - Experience in Javascript is a bonus - Strong experience with Llama.cpp and ggml inference engines - Good understanding of deep learning concepts and model architectures - Experience with transformers, LLMs, Diffusion models - A degree in Computer Science, AI, Machine Learning, or a related field Requirements - Demonstrated ability to rapidly assimilate new technologies and techniques Benefits - Remote flexibility: Work where and how you work best - we trust you to deliver - Fair compensation: Competitive salary + benefits that matter (medical, learning) - Ownership opportunities: See a problem worth solving? Own it. We back smart risks over bureaucratic safety - AI enhancement: We leverage AI to make you faster and stronger - complementing your abilities, not replacing them - Learning investment: English classes, professional development - Career progression: Real paths up, not just sideways shuffling - Responsive teammates: No ignored Slacks, no "not my problem" attitudes - Supportive culture: When you're stuck, people help. When things break, we fix them together - Human connections: Regular meetups, tech talks, and actual relationships beyond work