Senior Developer Relations and Community Manager - Brave Search API

Key Responsibilities

• Developer Adoption and Enablement: Drive developer adoption of the Brave Search API by making it easy to get started and succeed. Own onboarding resources that reduce friction from first API call to production use.
• Technical Content and Education: Create high-quality technical content including tutorials, sample applications, reference architectures, and interactive notebooks. Demonstrate real-world use cases across LLM, RAG, and agentic workflows.
• Documentation and Developer Experience: Treat documentation as a core product surface. Continuously improve clarity, usability, and completeness to optimize “time to first successful API call” and overall developer experience.
• Ecosystem and Integrations: Expand Brave’s presence across the AI developer ecosystem by building and supporting integrations with key frameworks and platforms (e.g., LangChain, LlamaIndex, Vercel AI SDK). Ensure Brave is a first-class option in developer workflows.
• Community Engagement: Build and engage with the developer community across channels such as GitHub, X, Discord, and forums. Answer questions, surface use cases, and establish Brave as a trusted solution for AI builders.
• Product Feedback and Market Insight: Act as “Customer Zero” by testing new features, identifying gaps, and channeling direct developer feedback to Product and Engineering. Provide insights on developer needs, friction points, and competitive dynamics.
• Launch Support (Technical): Partner with Product Marketing to support launches by delivering the technical assets required for adoption, including demos, code samples, and documentation updates.
• Developer Funnel Optimization: Improve conversion from signup to active usage by identifying friction points in onboarding, SDK usage, and implementation. Use data and feedback to increase activation and retention.

Requirements and Qualifications

• T-Shaped profile: Former engineer turned marketer, or PMM who learned to code.
• Native fluency in AI/Search: Knowledge of RAG, lexical vs. semantic search, context windows.
• Developer empathy: Experience with bad APIs, poor documentation, rate limits.
• Proven writing: Clear copy for landing pages and technical whitepapers.
• Technical chops: Comfortable with Python or JavaScript, cURL requests.

Bonus Points

• Experience at developer-focused companies (Vercel, Supabase, Stripe, HashiCorp, LangChain).
• Marketing data products or search infrastructure.
• Existing presence in AI/LLM builder community.

Compensation

United States: $150,000 - $200,000 DOE