Software Engineer, Forward Deploy - New Graduate

Parasail is building the AI Supercloud, helping AI teams deploy and scale inference across a distributed network of GPUs. We make it easier for developers to bring AI applications into production with the performance, reliability, and flexibility they need.

We’re looking for 2027 graduates who love building software, are curious about AI, and want to work directly with the people using what they build. As a Forward Deployed Engineer, you’ll help customers turn ideas into working applications—and use what you learn to make Parasail better.

You’ll work at the intersection of software engineering, AI infrastructure, and customer problem-solving. Working alongside experienced engineers, you’ll help customers understand their requirements, build and test solutions, and bring real workloads into production.

You’ll write code, investigate technical problems, and see firsthand how your work affects a customer’s product. You’ll receive guidance and mentorship while taking on increasing ownership of projects from initial discovery through deployment.

Example projects may include:

• Customer integrations: Build integrations and example applications that connect customers’ products to Parasail’s inference platform.

• Prototypes and evaluations: Turn a customer’s use case into a working prototype, then evaluate model quality, latency, throughput, and cost against their needs.

• Production deployments: Help customers move from a successful experiment to a reliable deployment, working through issues such as concurrency, retries, streaming, and error handling.

• Performance investigations: Reproduce and diagnose issues across application code, API integrations, and inference workloads, partnering with engineering to resolve them.

• Reusable developer tools: Turn lessons from customer projects into examples, documentation, and tooling that help the next developer get started faster.

You’ll also bring customer feedback into product and engineering discussions, helping the team identify improvements that benefit many users.

• Completing a bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field in 2027, or equivalent practical experience.

• Experience building software through coursework, internships, research, open-source contributions, or personal projects.

• Proficiency in at least one programming language, such as Python, Type Script, or Go.

• A foundation in software engineering fundamentals, including data structures, APIs, testing, and debugging.

• Clear written and verbal communication, with an interest in explaining technical ideas and understanding other people’s goals.

• Resourcefulness when facing an unfamiliar problem: you ask thoughtful questions, test assumptions, and follow through.

• Curiosity about AI models, inference, and what it takes to run AI applications in production.

• Enthusiasm for working directly with customers and collaborating in a fast-moving startup.

We don’t expect you to arrive as an expert in AI infrastructure. We’re looking for strong fundamentals, evidence that you enjoy building, and a willingness to learn.

• Projects using LLMs, open-source models, or inference APIs.

• Familiarity with cloud infrastructure, Linux, containers, or distributed systems.

• Experience measuring application performance or evaluating model outputs.

• Experience helping others solve technical problems through teaching, tutoring, technical communities, or customer-facing work.

• Build for real users. Work directly with developers and see your contributions become part of their applications.

• Learn across the stack. Develop practical experience in AI applications, inference infrastructure, and production engineering.

• Grow through ownership. Take on meaningful projects with support from experienced teammates.

• Help shape the product. Turn what you learn from customer deployments into improvements to Parasail’s platform and developer experience.

If you’re excited to build, learn quickly, and help developers bring AI into production, we’d love to hear from you.