• Build and ship Android features using Kotlin. • Create clean mobile flows for insurance, payments, claims, renewals and financial services. • Work with product and design to simplify complex user journeys. • Integrate backend APIs and ensure mobile flows are stable, secure and reliable. • Improve app performance, crash rate, loading states, responsiveness and memory usage. • Use analytics, user behaviour and production issues to improve the product. • Build AI-assisted mobile experiences only where they genuinely improve the user journey.

• Your responsibilities as a technical mentor will be divided into three major tasks: 1:1 video calls, Virtual Technical Deep-Dive Sessions, Group Q&A sessions • Provide personalized support by addressing learner questions related to course content and projects • For concept deep-dives, mentors will come prepared with a slide presentation that reviews a Nanodegree concept in more detail • Host regular sessions (via Slack or video) to address learner queries related to projects and coursework

• Diseñar y construir flujos de agentes de punta a punta sobre nuestra plataforma • Tomar decisiones de arquitectura de cada solución • Construir y mantener endpoints en FastAPI • Diseñar y afinar los sistemas de recuperación de conocimiento

• AI platform strategy — what tools, models, platforms, and patterns we use, when, and why. • Build vs. buy vs. adopt decisions, backed by real experience and opinions you can defend. • Evaluate, select, and deploy workflow / orchestration platforms, model providers, vector stores, MCP servers, agent frameworks, observability tooling. • Hands-on build and operations — deployment, scaling, upgrades, integrations with Slack, Atlassian, Databricks, AWS, internal databases. • Security and governance (with our vCISO) — secrets management, sandboxing, access controls, data classification, prompt-injection defense, audit logging, human-in-the-loop rules for high-stakes workflows. • The knowledge / RAG layer — ingestion pipelines, embedding strategy, retrieval quality, freshness. • Enablement — reusable templates, primitives, documentation, and debugging support so the AI adoption lead and business users can build workflows on the platform without needing you in the loop. • Model access, routing, and cost — API keys, rate limits, per-workflow / team / user cost tracking, model selection per use case, fallback strategies. • Platform health — uptime, cost, usage, incidents, security posture. Own the on-call.