$200,000–$250,000
AI Product Engineer
Updated
Pay not postedSan Francisco, CAOn-site
Samba TV seeks an AI Product Engineer to build and deploy production-grade AI agents that automate internal workflows across the company.
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At a glance
Posted base pay
Not posted
Median $190K
Typical senior FDE payMiddle 50% of 1,803 postings$160K–$220KThe work
Builds for teams inside the company
Balance
- Mostly building
- Mixed
- Mostly pre-sales or support
Project stages
- Pre-sales (not covered)
- Proof of concept (not covered)
- Implementation
- Operations
- Coding
- Writes production code
- Builds for
- Internal teams
- Level
- Senior
- Role
- Individual contributor
What they ask for
Tools
Less common in FDE jobs
- Who you build for: Internal teams14%
- Company size: About 201–1,000 people18%
- Company stage: Later private33%
- On-site37%
Share of US FDE postings that state each fact.
The job description from Samba TV
Posted by Samba TV on
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.
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
Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller.
About Samba TV
Samba TV uses automatic content recognition embedded in smart TVs to measure cross-screen viewership and power audience targeting and ad measurement for brands and agencies.
Private Late · 200–500 people
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