• Build and evolve the internal AI platform — a shared layer (model routing, prompt versioning, tools registry, memory, observability, and cost) separated from each area’s solution, with a paved path and self-service for tech and non-tech teams. • Own end-to-end architecture decisions for agentic/agent-based systems: orchestration, state, idempotency, retry/durability, RAG, model selection and routing, build vs. buy — planning, executing, and observing. • Measure the effectiveness of AI solutions (RAG effectiveness, agent reliability, hallucination rate) using evaluation and regression datasets, and use the numbers to decide — not just to monitor. • Share knowledge and raise the company’s AI bar: provide trainings, materials, and scalable best practices that extend usage beyond the team, translating non-technical area needs into solutions. • Participate in strategic projects hands-on, coding high-impact deliverables on short timelines when that moves a meaningful business metric. • Make and document architecture decisions with clear trade-offs, cost estimates, and impact. • Promote a culture of observability, security, and performance in AI solutions.

• Build and ship end-to-end product experiences across modern web applications, owning delivery from early concept through production release and iteration. • Rapidly prototype new concepts, validate feasibility and user value, and graduate successful prototypes into secure, scalable, maintainable production services for the first set of customers. • Design and manage AI-powered capabilities across retrieval, context shaping, and personalization (RAG, context engineering, collaborative filtering, content-based filtering, etc.), balancing quality, safety, privacy, and latency. • Build or leverage API-first, versioned REST microservices that expose domain capabilities in a consistent, reliable way across experiences. • Apply AI agents and modern developer tooling to speed up development workflows, including scaffolding, code generation, evaluation, debugging, and test automation. • Establish engineering clarity and alignment through strong technical communication and documentation (e.g., architecture briefs, API specs, runbooks, decision records). • Champion pragmatic software quality practices: code reviews, automated testing, CI/CD, observability, performance tuning, and cloud cost-aware design. • Partner closely with Product, Design, Research, Data Science, and customer-facing teams to translate needs into working software that meets business outcomes. • Ensure regulatory, compliance, security, and privacy expectations are met throughout development and release. • Independently create a test strategy (unit/integration/e2e) aligned to risk, including security testing. • Write architecture briefs and proposals (lightweight but clear), run experiments, and document tradeoffs. • Integrate telemetry for performance, reliability, availability, and usage insights. • Perform other duties as assigned.

• Build and own core Dashboard infrastructure, including the application shell, navigation, layout patterns, shared components, and product surfaces used across Nylas. • Design and implement full-stack product experiences across frontend, backend APIs, data models, permissions, service integrations, and deployment paths. • Modernize the Nylas Dashboard into a fast, polished, cohesive control plane for developers and technical teams. • Build AI-native and agent-facing experiences that help users configure products, understand errors, debug integrations, apply best practices, and operate Nylas more effectively. • Work across Nylas product areas, including Email, Calendar, Scheduler, Notetaker, Inbound Email, Transactional Send, Domains, Logs, and Agent Accounts. • Partner with backend and platform teams to design clean APIs and service boundaries that support excellent user experiences. • Drive performance as a product feature. Profile, measure, and optimize Dashboard interactions so the product feels fast and responsive. • Create reusable abstractions and shared patterns that help other engineering teams ship product surfaces consistently. • Improve onboarding, activation, self-serve configuration, troubleshooting, and product discovery across the Dashboard. • Use AI-assisted development tools to accelerate implementation, improve quality, explore product behavior, and help define how AI fits into Nylas’ engineering workflows. • Ship incrementally and continuously, using customer feedback, product intuition, and technical judgment to improve the platform every week. • Collaborate closely with Design, Product, Customer Success, Solutions Engineering, and Developer Relations to translate customer feedback into product improvements.

• Design and develop responsive user interfaces, backend services, APIs, and data-driven applications using JavaScript and TypeScript technologies • Work across the application stack, building engaging React-based user experiences while developing Node.js services • Integrate with PostgreSQL databases • Engage with and motivate clients while diving into both frontend and backend development • Identify opportunities for future improvement • Drive quality, collaboration, and innovation as part of our team