AI Infra Engineer

Who Is Serotonin Serotonin is the top go-to-market firm for transformative technologies, specializing in marketing, strategy, recruiting, and legal services. With a global team of 90 across 15 countries, Serotonin has supported over 300 clients in consumer tech, crypto infrastructure, digital assets, venture capital, and AI since its launch in 2020. Delivering end-to-end go-to-market solutions across all major marketing channels, including public relations, growth marketing, on-chain analytics, content, research, social, and design - Serotonin accelerates global innovation. At the core of our business is the Serotonin Platform, serving as a central nucleus for the crypto ecosystem, connecting builders and founders with essential resources to drive business growth.

About The Role We’re building an intelligence layer at Serotonin, and we need someone to own it end to end.

This role sits at the intersection of competitive intelligence, data engineering, and agentic AI. You’ll pull signals from social platforms, on-chain activity, and paid media, and turn them into structured intelligence that shapes how we run accounts and campaigns, both internally and for clients.

This is a systems role, not a workflow automation role. You’ll design and maintain the data pipelines, agentic workflows, and full-stack applications that make our intelligence capabilities real and repeatable. The best outcome isn’t a one-off solution for one team, rather it looks like a system three teams depend on independently six months from now.

You’ll work directly with marketing leads and client teams, understand how they actually operate before you build anything, and ship things that are live, used, and measurable.

Responsibilities

• Build and maintain agentic systems that continuously collect, process, and surface signals from social platforms, on-chain data, and ads ecosystems. Turn raw, multi-source data into structured intelligence that informs real account and campaign decisions
• Design and maintain the pipelines that power those systems: ingesting from multiple external APIs, enriching and modeling data, and building semantic layers that both humans and AI agents can actually use
• Build multi-step AI agents that automate research, synthesis, monitoring, and reporting. Not single-call LLM wrappers, but orchestrated systems with memory, defined tools, and structured output schemas that teams can depend on
• Build full-stack applications and dashboards that make intelligence accessible across client accounts. Live tools, not decks
• Spend real time with internal teams across marketing, PR, content, growth, and social before writing a line of code. Map how work actually moves, identify where signal gaps create friction, and build systems that solve for multiple teams from a single architecture
• Stay ahead of the AI tooling landscape. Know when a no-code connector is the right call and when you need to build. Define how impact gets measured, and build the reporting to prove it

Requirements Software Engineering (non-negotiable)

• Python, fluently: pipelines, agent systems, data processing, scripting
• Active GitHub with meaningful commit history, not forks and tutorials
• REST and GraphQL API experience building integrations, not configuring connectors
• SQL: schema design, not just pulling rows
• Full-stack development: Next.js or equivalent; you’ve shipped something users interact with in production
• LLM API usage: building directly with Anthropic or OpenAI APIs, including agent orchestration frameworks (LangGraph, CrewAI, or custom)
• Vector databases and RAG: embeddings, retrieval pipelines, semantic search

Intelligence and Signal Layer

• Experience ingesting and fusing data from multiple external sources: social APIs (X, LinkedIn), ads APIs (Meta, Google), or similar multi-source environments
• Ability to translate raw signal into structured, actionable output for non-technical stakeholders
• Experience building dashboards or reporting layers others depend on operationally, not just internal notebooks

AI Tooling

• No-code tools (Make, n8n, Zapier) are part of your toolkit but they don’t act as the foundation of your practice. You reach for them when they’re genuinely the fastest path to a reliable outcome. A strong developer who knows when to use no-code will always outperform a no-code specialist who can’t own the harder technical work

***On-Chain Data (strong plus…