Senior Applied AI Engineer

We’re a fully remote team, globally distributed, deeply collaborative, and seriously passionate about building the future of software development.

This is your chance to join a small team with a big vision. If you love shipping fast, solving real problems, and pushing the boundaries of what’s possible, we’d love to meet you.

Join us on the forefront of AI-powered development as we revolutionize how software gets built. As a Senior Applied Engineer, you will be the driving force behind our AI agents that transform natural language into production ready applications. You will work with state-of-the art LLMs, pioneering new ways to make AI understand, reason about, and generate complex full-stack applications. This isn’t just about integrating APIs, instead it’s about pushing the boundaries of what AI can do to empower our users to build stunning apps.

As part of this role, you will work in an interesting problem space and tackle challenges like maintaining context across large codebases, orchestrating multi-step workflows that feel intuitive to users, and making sure our AI agents can handle everything from simple UI changes to complex architectural decisions. Your work will directly impact how millions of users bring their ideas to life.

This is a unique opportunity to shape the future of AI-assisted development in a fully remote, globally distributed team that ships fast and thinks big. If you are passionate about making AI more capable, reliable, and accessible to builders everywhere, this role offers the perfect opportunity to innovate and see your work deployed at scale.

• Develop AI Agents: Design and implement AI agent features and extend existing agents with new capabilities. This includes managing the agent’s context (using techniques like sub-agents, retrieval based context management, sliding context windows, etc.) so it can handle long conversations or large knowledge and code bases efficiently.
• Integrate Multiple LLM Providers: Leverage models from providers such as OpenAI (GPT series), Anthropic (Claude), and Google (Gemini). Quantitatively evaluate and choose the best model for a given task, and incorporate new model features or improvements (often by beta-testing new releases and assessing their strengths).
• Tool Use and Workflow Orchestration: Enable the AI agent to call external tools and APIs safely and effectively. Implement structured approaches to allow the agent to perform actions like web searches, database queries, fetch additional information, or other domain-specific operations. Utilize frameworks such as Vercel’s AI SDK, Lang Graph and others for building multi-step AI workflows.
• Team Collaboration
  :
  Work closely with your immediate team and adjacent teams to deliver AI-powered features. Collaborate effectively with peer engineers and product managers to ensure AI-driven features are production-ready, efficient, maintainable, and well-monitored in deployment. Share knowledge and help lift up mid-level and junior engineers on the team.
• Data Collection and Analysis
  :
  Collect and curate datasets from agent responses and multi-turn conversations to understand agent behavior. Analyze conversation patterns, failure modes, and success signals to derive actionable insights that drive improvements to agent performance and user experience.
• Continuous Improvement and Evaluation: Stay up-to-date with the latest research in NLP and LLMs, and experiment with novel techniques (e.g. new prompting strategies, context handling methods, model fine-tuning opportunities). Continuously evaluate the AI system’s performance using systematic tests and user feedback, and iterate on prompts, agents and workflows to improve output quality and reliability (for example, by developing automated LLM evaluation benchmarks).
• Type Script Proficiency: Strong proficiency in Type Script is essential, as it's our primary programming language for building AI agent systems and integrations.
• LLM
  
  Experience:
  
  Hands‑on experience working with Large Language Models (LLMs) and understanding their capabilities and limitations. Proven experience building applications or systems powered by LLMs.
• Prompt…