• Lead production-grade healthcare AI systems: scale distributed Python-based agents, own end-to-end delivery with real patients, in a lean team; make care accessible. • Deploy and refine AI-driven patient communication and triage systems directly with hospitals and clinics. • Architect and scale agent orchestration systems built on LLMs and agentic frameworks. • Build and maintain secure healthcare data layers with low-latency voice and video capabilities. • Scale distributed systems under real clinical load. • Work in a small team which means you own things end to end, not hand them off.

• Develop and maintain features on our Next.js (App Router) frontend using TypeScript, SWR, Tailwind, and a component-driven design system, with full internationalization (i18n) support. • Design, implement, and maintain RESTful APIs with NestJS (TypeScript) to manage authentication, data processing, billing, usage tracking, and orchestration of AI workflows. • Own backend services end-to-end: from schema design and migrations to deployment and observability, and contribute to new services as the product surface grows. • Integrate and maintain third-party SDKs and APIs that power critical product flows, including payment processing, authentication, analytics, and messaging. • Build AI agents and tools using the Claude SDK and Model Context Protocol (MCP): giving LLMs real-time access to data, APIs, and tools so they can take meaningful actions on behalf of users. • Contribute to schema design with Prisma and PostgreSQL, write and review migrations, and reason carefully about data models that evolve safely over time. • Implement and maintain feature flags, A/B experiments, and analytics events so product decisions are driven by data. • Handle incoming webhooks and asynchronous task processing with the rigor required for payment-critical and PII-handling code paths (idempotency, retries, fault tolerance). • Collaborate with AI product managers and AI specialists to translate complex requirements into robust, scalable features — and push back on complexity when a simpler path exists. • Collaborate on application deployment and help maintain our cloud infrastructure.

• Design scalable technical solutions in collaboration with local and distributed engineering teams • Partner closely with internal stakeholders and cross-functional teams to deliver high-quality features • Mentor and support junior engineers, contributing to team growth and engineering excellence • Work independently with strong ownership and adaptability to evolving business priorities • Write clean, maintainable, testable, high-quality code • Drive engineering best practices around testing, automation, and code quality • Ensure all solutions meet established quality and security standards • Participate in architecture discussions, design reviews, and code reviews • Analyze feature performance and define success metrics • Identify and troubleshoot performance bottlenecks • Apply secure coding principles and system security best practices • Contribute to technical documentation and system design artifacts

Role Description We are looking for a self-driven GTM (Go-To-Market) Engineer Intern who is pro at using AI tooling, automation and understanding the marketing landscape. This role is ideal for someone who enjoys building systems, experimenting with tools, and scaling outbound efforts using automation. You will build the outbound engine that drives CloudRaft's growth — enrichment pipelines, AI-personalized email sequences, LinkedIn automation, and lead scoring systems. These aren't experiments; they go live and generate real pipelines. You will work closely with the founder to design, execute, and optimize outbound campaigns while leveraging AI and no-code/low-code tools. Key Responsibilities - Create workflows and data pipelines to source data for marketing - Build and execute outbound marketing campaigns across email, LinkedIn, and other channels - Set up and manage automation workflows - Create and optimize automated lead generation and nurturing systems - Track, analyze, and optimize campaign performance - Run rapid experiments on new GTM channels and tools, measure outcomes, and document what works Qualifications - Background in Marketing, Computer Science, Engineering, or related fields - Strong interest in AI, automation, and growth marketing - Hands-on experience with tools like Claude or similar, n8n, Zapier, Make, or similar - Comfortable writing basic Python or using APIs to connect tools when no-code falls short - Experience prompting LLMs beyond chat — think structured output, classification, or agent-style workflows - Understanding of outbound marketing and lead generation - Comfortable building with AI tools and workflows - Problem-solving mindset with a bias for action - Ability to work independently in a remote setup with minimum direction Benefits - Work at the intersection of AI, marketing, and automation - Build real-world systems from scratch - High ownership and fast learning environment - Opportunity for a full-time role based on performance Duration 3–6 months | Remote