Design and build production-grade AI systems that leverage LLMs, agent frameworks, retrieval systems, and external tools.
Develop intelligent workflows that provide users with actionable insights and recommendations, not just chatbot-style interactions.
Help shape the evolution of AI-native product experiences across multiple surfaces, including web applications, APIs, developer tooling, and embedded workflows.
Improve system performance through optimization of retrieval, memory, context management, and tool orchestration.
Partner closely with customers and internal teams to understand emerging AI use cases and translate them into product capabilities.
Stay on top of advancements in AI models, agent architectures, and voice technologies, helping guide product and technical strategy.
Act as a resource for the broader team on AI best practices, workflows, and implementation approaches.
Contribute across the stack when needed, from backend AI infrastructure to customer-facing product features.
What They're Looking For
Strong experience building AI-powered products or features used in production environments.
Deep familiarity with LLM-based systems, including prompting, retrieval, evaluation frameworks, memory architectures, and tool usage.
A strong product mindset and the ability to identify where AI creates meaningful value versus unnecessary complexity.
High ownership and a willingness to take initiative in ambiguous, fast-moving environments.
Experience moving quickly from idea to implementation and shipping customer-facing solutions.
Curiosity about the future of conversational and voice-based AI systems.
Ability to work across backend services, AI infrastructure, and user-facing applications when required.
Strong communication skills and a collaborative approach to problem-solving.
Tech Stack
Python
LLM APIs and agent frameworks
Cloud infrastructure and distributed systems
TypeScript and modern web technologies
Internal developer tooling and automation platforms