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
- 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.
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
Not required, but you should be the kind of person who picks up a new data domain fast
- 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. Crypto experience is a meaningful plus.
Software Engineering (non-negotiable)
AI Tooling
On-Chain Data (strong plus)
Domain
This Role Is Right For You If...
You've built something end to end and you own it, not "contributed to" or "worked on the team that built it," but the person who designed it, shipped it, and is still maintaining it. You care more about making three teams faster than shipping something impressive that one person uses, and your GitHub actually reflects what you can do without needing to be asked for a portfolio.
You've probably come up through a founding engineer role, an early-stage startup, or as an independent builder, ideally somewhere in data, intelligence, or crypto. You pick up new domains fast and use AI as a core part of how you do that. You ship in days, you're not precious about being wrong early, and you know the difference between using AI as a multiplier versus using it to paper over a weak foundation.
We hire people who don't wait to be told what to build next, who take full ownership of their work from idea to maintenance, and who are just as effective working async with someone in Singapore as they are with someone in their timezone.
Benefits
- Competitive Salary
- Health Insurance (US Only)
- 401(k) (US Only)
- Remote Work Environment
- Parental Leave
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
