• Build a real SaaS from scratch: full-stack development (front/back), architecture, performance optimization, security, and scalability. • Integrate and leverage advanced AI tools: OpenAI, Anthropic, Mistral, specialized LLMs, embeddings, prompt engineering, autonomous agents, etc. • Create complex API pipelines: multi-API calls (Google, Notion, WhatsApp, Pennylane, accounting platforms…), webhooks, authentication, and real-time event handling. • Manage and optimize databases: clean schema design, performant queries, relationships, indexing, and migrations. • Implement analytical computations and business rules: data extraction, automated analysis, scoring, anomaly detection, and recommendation generation. • Prototype very quickly: build, test, iterate, discard, and repeat when necessary. • Participate in all technical decisions: stack selection, product roadmap, technical trade-offs, and prioritization. • Work with full autonomy: understand a business problem, propose a solution, implement it, and ship it. • Adopt an entrepreneurial mindset: be proactive, take initiative, challenge choices, and prioritize product impact above all.

• Develop and maintain a mission-critical payments API • Ensure code quality, security, and scalability • Collaborate with like-minded individuals to achieve the company's mission • Participate in company events like hackathons and offsites

• Build high-performing, scalable, enterprise-grade applications • Work as part of a talented team on mission-critical applications • Adapt to dynamic and collaborative work environments • Confirm project requirements and provide estimates • Own project success by proactively communicating risks and issues • Contribute to all phases of the development lifecycle • Code conforming to best practices and performs peer reviews

• Align and coordinate technical leads across roles and ensure architectural consistency across projects • Define and enforce engineering standards and own technological choices and selection of tooling for the practice. • Ensure consistent use of AI frameworks, orchestration layers, and integration patterns • Set standards for designing and implementing Agentic AI systems • Establish AI governance (traceability, explainability, compliance, monitoring) • Validate smart contract and distributed system architecture decisions • Ensure DevSecOps alignment in regulated environments • Partner with Product and Delivery leads to ensure realistic engineering planning • Identify technical risks early and drive mitigation strategies • Define and track engineering KPIs and promote automation and AI-assisted engineering productivity • Develop structured improvement initiatives and foster a culture of technical excellence and ownership.