Who We Are

At Seedtag, our mission is to transform advertising by proving that effectiveness and user privacy can truly coexist.

As the leading Neuro-Contextual Advertising Company, we combine Artificial Intelligence, Natural Language Processing, Computer Vision, and neuroscience to understand not only what content is about, but how it makes people feel and what they intend to do next.

Our proprietary AI, Liz, enables brands to connect with audiences across the open web and Connected TV without cookies or user tracking. Founded in 2014 by two ex-Googlers, Seedtag has grown to 500+ Seedtaggers in 17 countries, backed by €250M in funding, and operates today as a global ad-tech leader.

If you enjoy solving complex engineering challenges and building AI-driven systems at scale, you’ll feel right at home here.

Your Challenge

You will take technical ownership of key components of Liz Agent, Seedtag's AI agent platform, ensuring scalability, reliability, and seamless integration across teams.

Your Main Responsibilities Will Include

• Agent Platform Development: Design, build, and maintain the core Liz Agent runtime, including agent execution, context management, and event streaming.
• Tools & Integrations: Develop MCP tool servers, APIs, and authentication and policy services to enable secure agent access to internal data and capabilities.
• Agentic AI Innovation: Enhance agent capabilities through multi-model routing, memory, durable execution, and LLM frameworks.
• Reliability & Observability: Ensure platform stability, performance, and production debugging through monitoring, tracing, and evaluation tools.
• Platform Architecture: Define scalable APIs, service patterns, CI/CD pipelines, and cloud-native deployment standards that enable teams to build agents independently.
• Security & Quality: Implement robust security controls, prompt-injection protection, automated evaluations, and regression testing.
• Technical Leadership: Drive architectural decisions, mentor engineers, and collaborate with Data, ML, Platform, and Product teams.

Our Core Values

• Outcome over Output
• We measure success by impact and value, not by volume of features or lines of code.
• Failure Is Allowed, Learning Is a Must
• Experimentation is key to innovation. We test early, iterate often, and learn fast.
• We Are All Scouts
• We take ownership and leave things better than we found them.
• We Are Data-Driven
• Data informs our decisions and helps us continuously improve our systems and results.

Tech Stack

You'll work with the technologies powering Liz Agent, our AI agent platform, built on 30+ services running on GKE.

Our Stack Includes

• Languages: Python, Go.
• Cloud & Infrastructure: GCP, GKE, Kubernetes, Vertex AI, BigQuery.
• Agentic AI: MCP, PydanticAI, Claude Agent SDK, LangGraph, OpenAI Agent SDK.
• Data & Messaging: Pub/Sub, Redis, Firestore.
• LLMOps & Observability: Langfuse, Prometheus, Logfire, LiteLLM.
• DevOps & CI/CD: ArgoCD, Kustomize, GitHub Actions.
• Additional Technologies: TypeScript, Next.js, embeddings, vector search.

What You’ll Need to Succeed

• 5+ years of experience building and maintaining production backend systems.
• Strong Python expertise, including APIs, asynchronous programming, testing, and clean architecture.
• Hands-on experience developing LLM applications or AI agents in production.
• Solid understanding of event-driven architectures, microservices, Kubernetes, and cloud infrastructure.
• Experience with LLMOps, observability, CI/CD, and production troubleshooting.
• Knowledge of AI security, including authentication, access controls, and prompt-injection protection.
• Proven ability to lead technical decisions, mentor engineers, and work autonomously in a collaborative environment.

Why Join Seedtag?

• A key moment of growth with real ownership and global impact.
• Flexible work model with 100% remote or hybrid options. (Remote contracts available in Spain, Italy, UK, Belgium, Netherlands, France, and Germany.)
• Continuous learning through a learning platform and optional language classes.
• A supportive, trust-based culture that values well-being.
• Team activities, offsites, and opportunities to connect beyond work.

Additional Perks

• Home office setup budget up to €1,000
• Paid trips to our HQ in Madrid
• MacBook Pro M3

• Design, build, and maintain the core Liz Agent runtime, including agent execution, context management, and event streaming.
• Develop MCP tool servers, APIs, and authentication and policy services to enable secure agent access to internal data and capabilities.
• Enhance agent capabilities through multi-model routing, memory, durable execution, and LLM frameworks.
• Ensure platform stability, performance, and production debugging through monitoring, tracing, and evaluation tools.
• Define scalable APIs, service patterns, CI/CD pipelines, and cloud-native deployment standards that enable teams to build agents independently.
• Implement robust security controls, prompt-injection protection, automated evaluations, and regression testing.
• Drive architectural decisions, mentor engineers, and collaborate with Data, ML, Platform, and Product teams.

• Strong Python expertise, including APIs, asynchronous programming, testing, and clean architecture.
• Hands-on experience developing LLM applications or AI agents in production.
• Solid understanding of event-driven architectures, microservices, Kubernetes, and cloud infrastructure.
• Experience with LLMOps, observability, CI/CD, and production troubleshooting.
• Knowledge of AI security, including authentication, access controls, and prompt-injection protection.
• Python and Go
• GCP, GKE, Kubernetes, Vertex AI, and BigQuery
• MCP, PydanticAI, Claude Agent SDK, LangGraph, and OpenAI Agent SDK
• Pub/Sub, Redis, and Firestore
• Langfuse, Prometheus, Logfire, and LiteLLM
• ArgoCD, Kustomize, and GitHub Actions
• TypeScript, Next.js, embeddings, and vector search

• Proven ability to lead technical decisions, mentor engineers, and work autonomously in a collaborative environment.