Senior Software Engineer, Fullstack

Parasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads. The Role We’re looking for a Senior Fullstack Engineer who wants to own large surface areas of product from database to pixel. You’ll build the interfaces, APIs, and systems that thousands of AI engineers interact with daily — from our real-time inference dashboard and model deployment console to the orchestration APIs that route workloads across a global GPU network. This isn’t a role where you’ll be handed pixel-perfect mocks and asked to implement them. You’ll shape what we build and how it works, collaborating directly with founders and infrastructure engineers to turn complex distributed systems into products that feel simple and fast. What You’ll Build Inference Platform UI: Design and build the dashboards, model deployment workflows, and real-time monitoring views that our customers use to deploy and manage AI workloads at scale. APIs & Backend Services: Architect and implement the backend services that power our platform — model serving endpoints, usage metering, billing integrations, authentication, and developer-facing APIs. Orchestration Interfaces: Build the frontend and API layers on top of our GPU orchestration engine, giving users intuitive control over routing, caching, scaling, and cost optimization across our global network. Developer Experience: Own the end-to-end developer experience including API documentation, SDK design, CLI tools, and onboarding flows that make Parasail the easiest inference platform to adopt. Real-Time Systems: Implement streaming interfaces (SSE/WebSockets) for real-time inference responses, live cost tracking, and deployment status updates. Data & Analytics: Build internal and customer-facing analytics — usage dashboards, cost breakdowns, latency distributions, and performance benchmarking tools. Technical Abilities Frontend Engineering: Strong experience with modern frontend frameworks (React, Next.js, or similar). You write clean, performant TypeScript and care about UI/UX details — loading states, error handling, responsive design, and accessibility. Backend Development: Deep experience building production backend services in Go, Python, Java, or Node.js. You’re comfortable designing RESTful and gRPC APIs, working with relational and NoSQL databases, and implementing auth, rate limiting, and caching layers. Distributed Systems Fundamentals: Solid understanding of distributed computing principles — consistency models, fault tolerance, and scalability patterns. You don’t need to be a distributed systems PhD, but you should be comfortable reasoning about systems that span multiple services and regions. Cloud-Native & Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and CI/CD pipelines. Bonus if you’ve worked with Infrastructure as Code (Terraform, Pulumi). Data & Observability: Experience building data pipelines, analytics dashboards, and integrating observability tools (metrics, logging, tracing). You know how to instrument systems so problems surface before customers notice. AI/ML Familiarity (Nice to Have): Understanding of LLM technologies, inference optimization (batching, caching, quantization), or model serving platforms like vLLM, TGI, or Triton. If you don’t have this yet, you’re excited to learn. Qualifications 5+ years of professional software engineering experience with significant fullstack ownership (you’ve shipped features end-to-end, from UI to database). Track record of building and scaling web applications or developer platforms used by technical audiences. Experience working in fast-paced environments where you’ve had to make pragmatic trade-offs between speed and quality.