What you will do

• Build a highly scalable data-driven SaaS platform that can easily connect to other IT systems.
• Build our virtual assistant platform and applications leveraging cutting-edge LLMs. You'll build a product using voice and text communication with human-like capabilities.
• Build various front-end applications for B2B customers, consumers, and internal admins.
• Build our “AI Studio” for automated and manual grooming and labeling of various training data sets.
• Define the product: Collaborate with the product managers to clearly understand and refine product requirements, aligning them seamlessly with our business goals.
• Define the software architecture and code the product.
• Apply ML as a major differentiator for the product (you do not need to be an ML engineer yourself).
• Integrate with various tools for CI/CD, test automation, monitoring, logging, and documentation.

What we look for

• BSc. or MSc. in Computer Science or comparable degree.
• At least 5 years of hands-on coding experience as a full-stack engineer.
• Exceptional problem-solving abilities, effective communication, and teamwork skills.
• Backend DevelopmentExperience with event-driven architectures and mechanisms. Comfortable defining and building robust APIs with a strong understanding of different protocols like Websockets, REST, RPC frameworks, etc. Experience with database schema design and an understanding of query performance. Deep appreciation for building applications with observability as a first-class principle and familiarity with application performance monitoring. Extensive experience coding in Go or motivation to learn it. Experience in Python is a plus. Experience with backend services on AWS.
• Frontend DevelopmentKnowledge of modern front-end ecosystems and experience applying frameworks/tools (React.js, Webpack, and Node.js) and patterns to complex web applications. Extensive experience coding in TypeScript.
• CI/CD (nice to have): Familiar with CI/CD processes and tools like Terraform, Fargate, Docker, etc.
• Applied ML (nice to have): Familiar with LLMs and prompt engineering or even better experience in fine-tuning LLMs.