AI Product Engineer

What you'll do

• Build and deploy AI agents using modern agent SDKs (Claude, OpenAI, or similar) with custom tools and function calling
• Design and build tool harnesses and execution environments for agents on desktop and cloud
• Partner with internal teams to understand workflows, identify automation opportunities, and build tailored agents
• Think critically about LLM capabilities and limitations
• Develop context engineering strategies for LLMs within token limits
• Build and maintain custom tool libraries for agents to interact with internal systems, APIs, and data sources
• Deploy and manage agents in cloud environments with monitoring, error handling, and cost controls
• Optimize LLM costs and performance through prompt engineering, caching, and model selection

Requirements

• Built AI agents and shipped them to production
• Deployed agents in cloud environments
• Built tools, harnesses, or scaffolding for agents
• Daily use of Claude Code and Cursor
• Deep comfort with AI-assisted development including headless mode, multi-file editing, MCP server integration
• Critical understanding of LLMs and their inner workings
• Knowledge of differences between models (Claude, GPT, Gemini, open-source)
• Strong product sense focused on user needs
• Pragmatic approach to shipping solutions quickly and iterating
• Ability to translate non-technical team pain points into effective agents
• Ownership and drive from idea to impact
• Clear communication of complex AI systems
• Staying current with AI landscape and bringing new ideas
• Comfortable with cloud platforms (GCP, AWS, Azure) and containerized environments
• Experience with advanced agent patterns or multi-agent systems
• Experience building and configuring MCP servers
• Open-source contributions to AI/ML projects
• Familiarity with observability tools for LLM applications
• Media, ad tech, or streaming data domain knowledge

Tech stack