Remote Software engineering Jobs · LLMs

Join a pre-sales team driving the adoption of AI and event-driven architecture solutions. Engage with enterprise customers to design and demonstrate innovative technical solutions. Lead technical discovery sessions, provide guidance on solution implementation, and support sales strategies.

• Own end-to-end implementation of AI-powered product features, from prototypes to production.
• Mentor other engineers on the team, leveling up the team as a whole.
• Collaborate across the organization to support shipping these features to production.

• Build and evolve Rasa’s core Conversational AI engine, leveraging LLMs.
• Lead architecture decisions and algorithm implementations.
• Collaborate with engineers to build Rasa Pro, enabling developers to build, deploy, and maintain complex AI assistants.

• Review AI-generated responses and evaluate technical accuracy.
• Provide expert feedback to train AI systems to write better code.
• Work with various programming languages and coding challenges.

• Design, develop, and maintain a robust platform to enable users to create and manage AI agents.
• Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability.
• Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios.

• Develop and test features involving LLMs, automation pipelines, or AI-driven tooling.
• Assist with model evaluation, data preparation, and prompt engineering.
• Build lightweight prototypes and internal tools to accelerate experimentation.

• Develop and maintain internal tools and systems that automate existing work and increase employee productivity using AI.
• Collaborate with teams across the business to understand pain points and identify high-impact automation opportunities.
• Rapidly prototype small AI-enabled utilities or automations and deploy them into production swiftly.

Serve as a public-facing expert and ambassador for Bolt.new across social platforms, answering questions with empathy, clarity, and confidence. Troubleshoot and resolve technical issues, providing fast, high-quality support via email, and (occasionally) video calls. Surface insights and patterns from the community, turning feedback and sentiment into actionable input for Product and Engineering.

Serve as the technical authority on AI-driven, event-based architectures. Design reference architectures, prototypes, and proof-of-concept solutions. Collaborate with sales teams to strategize and accelerate pre-sales cycles.

• Design, develop, and maintain machine learning infrastructure, tooling, and models.
• Enable cross-functional teams to understand data lifecycles and ML patterns.
• Build internal platforms and services to integrate AI capabilities into customer-facing features.