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At Similarweb, a publicly traded digital intelligence platform serving thousands of customers globally including Google, eBay, and Adidas, you will join the AI Platform team to build the foundational infrastructure that enables AI adoption across the entire organization.
Your mission is to architect and develop a company-wide AI platform that serves as the foundation for dozens of AI use cases and workflows. Rather than having each team solve the same problems independently, you will build the shared infrastructure that turns AI experiments into reliable production systems.
Key responsibilities include:
- Design and build the core agent platform, including runtime, orchestration, state and memory management, and a shared agent SDK that teams across the company use instead of rebuilding foundations.
- Build and operate the tool and connector layer, including MCP servers that expose Similarweb data, internal systems, and third-party services to agents in a consistent, safe way.
- Develop LLM-based agents for high-value internal workflows and extract reusable parts back into platform capabilities.
- Implement integrations that let agents take automated actions on behalf of users, streamlining workflows and reducing manual overhead.
- Establish secure-by-default patterns: permissioning and data-access boundaries, PII handling, prompt injection defenses, and audit logging in line with Similarweb's security and privacy standards.
- Continuously evaluate and improve the performance of AI models and agents to ensure high-quality, data-driven results.
Your users are Similarwebbers—engineers, analysts, data scientists, and business teams across the organization—and your work enables them to ship agents and AI-powered workflows in days rather than quarters. This is a high-leverage, horizontal role with company-wide impact.
Similarweb offers a hybrid work model (3 days in office, 2 days remote), modern office space in Prague's DOCK IN area, 5 weeks vacation, birthday day off, equity, top-tier hardware (MacBook Pro M5, dual monitors, standing desks), and career growth opportunities in leadership or technical tracks.
REQUIREMENTS:
- 5+ years of software engineering experience with strong proficiency in Python
- Hands-on experience with LangGraph, LangChain, or similar frameworks for building AI agents
- Strong understanding of LLMs, prompt engineering, and AI agent architectures
- Solid grounding in production engineering: REST APIs, asynchronous services, integrating external data sources, containers, and CI/CD
- Strong collaboration and communication skills, including with non-engineering stakeholders
PREFERRED SKILLS:
- Familiarity with the AI Agents ecosystem, including different LLM providers, vector store solutions, MCPs
- Experience evaluating LLM performance and quality, and with LLM observability tooling
- LLMOps experience: cost and latency optimization, semantic caching, model routing, capacity planning
- Experience designing RAG systems over large or heterogeneous data sources
- Awareness of AI-specific security and safety concerns in multi-tenant internal platforms
- Familiarity with cloud environments (especially AWS), Kubernetes, and infrastructure-as-code
