AI Product Engineer

United States·San FranciscoUS Full-time Salariedmid

EngineeringData ScienceOtherProduct EngineerAi Product Engineer

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anthropicawsazuregcpopenaistreaming-data

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant.

Join our AI Task Force to build production AI systems that improve how we develop software and work with data. You’ll design and ship autonomous agents, tool harnesses, and intelligent workflows that solve real problems for our teams.

A core part of this role is working closely with internal teams—understanding their workflows, identifying where agents can help, and building solutions tailored to their needs. You’ll need to think critically about how LLMs actually work, what they’re good at, and where they fall short.

Our team builds with Claude Code, Cursor, and other AI-assisted development tools daily—you should be deeply comfortable in these environments and excited to push them further.

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—both on desktop (local CLI, IDE integrations) and in the cloud (containerized, API-driven)
Partner with internal teams across the organization to understand their workflows, identify automation opportunities, and build agents tailored to their use cases
Think critically about LLM capabilities and limitations—understand the differences between models, when to use which, and how to get the best results from each
Develop context engineering strategies—understanding how to give LLMs the right information at the right time within token limits
Build and maintain custom tool libraries that agents can use to interact with internal systems, APIs, and data sources
Deploy and manage agents in cloud environments with proper monitoring, error handling, and cost controls
Optimize LLM costs and performance through prompt engineering, caching, and smart model selection

You’ve built AI agents and shipped them to production—not just prototypes

You’ve deployed agents in cloud environments and dealt with the real-world challenges that come with it

You’ve built tools, harnesses, or scaffolding that agents use to accomplish tasks

You use Claude Code and Cursor daily—you’re deeply comfortable with AI-assisted development, including headless mode, multi-file editing, and MCP server integration

You think critically about LLMs—you understand how they work under the hood, not just how to call an API

You understand the differences between models (Claude, GPT, Gemini, open-source) and can reason about which to use for a given task

You have strong product sense—you focus on what users actually need, not just what’s technically interesting

You’re pragmatic—you ship 80% solutions quickly and iterate based on feedback

You can sit with a non-technical team, understand their pain points, and translate that into an agent that actually helps

You take ownership and drive things from idea to measurable impact

You communicate clearly—you can explain complex AI systems to anyone in the company

You stay current with the rapidly evolving AI landscape and bring new ideas to the team

You’re comfortable working across cloud platforms (GCP, AWS, Azure) and containerized environments

Experience with advanced agent patterns or multi-agent systems

Experience building and configuring MCP (Model Context Protocol) servers

Open-source contributions to AI/ML projects