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.
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—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
WHO YOU ARE
- 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
- Familiarity with observability tools for LLM applications
- Media, ad tech, or streaming data domain knowledge
What We Do
Television remains a vibrant cultural influence and an essential source of entertainment and information worldwide. Tremendous growth in content choices, and viewing platforms that allow us to watch anything, anytime, on any screen, has actually made it harder for viewers to discover and keep up with all the great programming available. It’s also more competitive for content providers to keep your attention, and for marketers to make strong, measurable connections with their target consumers. Technology that improves the viewing experience, enables content discovery, and addresses audience fragmentation across screens will strengthen television’s business model and relevance to consumers. Data is at the center of any solution to make TV better. Samba TV's technology is built into Smart TVs and easily maps to smart phones and tablets. By recognizing what's on screen, Samba TV learns what viewers like and using machine learning algorithms, enables discovery of shows and actors in a whole new way. Likewise, our data and measurement products are transforming the way stakeholders across the media landscape are thinking about their business. Given the dramatic growth in streaming services, connected devices, time-shifting, and multi-screen viewership, our data products solve real problems and create a meaningful competitive advantage for our clients.
