Serotonin is the top go-to-market firm for transformative technologies, specializing in marketing, strategy, recruiting, and legal services. They are seeking an AI Infra Engineer to build and maintain systems that collect and process data to enhance their intelligence capabilities, working closely with marketing teams to ensure the solutions are effective 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:

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
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
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
Working knowledge of how GTM and marketing teams operate day to day: PR, content, growth, social. Enough to know where intelligence systems create real leverage
Dune Analytics or equivalent SQL querying against on-chain data
Familiarity with wallet activity, token flows, and what on-chain behavior signals about an entity or protocol
Crypto experience is a meaningful plus

Serotonin

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Engineering

AI Infra Engineer

AI Infra Engineer

AI Infra Engineer