Founding Marketer at B2B Start Up (San-Fran Onsite)
Founding Marketer at Brainbase Labs (San-Fran Onsite)
Comp: $120K - $170K DOE + Equity
Onsite 100% San Francisco- Downtown
No sponsorship/Visa/Relo
About this role
We're building the first AI Workforce. We believe every company will soon have AI Employees working alongside their human team—handling conversations, operations, and workflows end-to-end. Brainbase is the platform that makes this possible.
In just over a year, we’ve grown from zero to $XM+ ARR, with customers ranging from fast-growing SMBs to Fortune 50 enterprises. We’re well-funded and backed by top investors, and our team is a multi-national team coming from Harvard, Stanford, Berkeley, and more. We care about results, ownership, and hunger.
We're scaling Brainbase Conversational, a platform designed for teams across industries to build, test, deploy, observe, and autonomously improve conversational agents. We're currently live in over ~150 deployments across automotive, hospitality, and enterprise, and want to build out our marketing motion for the product.
This is a Founding Marketer role for our Brainbase Conversational product. There is no playbook to follow—you’re helping build our marketing playbook from scratch. Your job is to build and own our marketing motion, with inbound leads as the primary focus. You'll be defining our brand, messaging, and owning our online and social presence.
What You'll Do
Define Brainbase’s positioning, messaging, and narrative across the website, sales collateral, and product
Build the initial demand engine: content, events, webinars, partnerships, and experiments that generate real pipeline
Work hand-in-hand with sales to craft ICPs, refine messaging, and turn objections into assets
Create thought leadership around AI Employees, applied AI, and the future of work—without hype or fluff
Launch and scale campaigns across owned and paid channels, iterating aggressively based on signal
Develop customer stories, case studies, and proof points that make the product feel obvious to buy
Establish early brand standards (visual, voice, tone) and enforce them with taste and discipline
Instrument marketing performance and report clearly on what’s working, what’s not, and why
2 - 7 years of experience doing generalist marketing for a B2B startup
About Brainbase Labs
Brainbase Labs is an applied AI research lab enabling AI in the workforce by building high-fidelity agent environments and tooling.
Our thesis is that as AI costs asymptotically converge to the cost of energy, the proliferation of AI employees will not come from best of batch vertical point solutions with SaaS margins, but rather from a single entity that will act as the workforce supplier of the entire global economy charging a small X% tax on each "worker minute".
Why is this possible?
Point solutions are not scalable. The unprecedented demand for forward deployed AI engineers is a strong sign towards enterprise AI adoption requiring a more flexible approach than the familiar one-size-fits-all SaaS model.
Vertical AI companies are a race to the bottom. The lack of differentiation and low switching costs for vertical AI solutions create a commoditized market where margins tend to zero in the long run.
Knowledge work is environment-constrained. We predict that the automation of a significant portion of economically viable knowledge work as it stands right now is primarily environment-constrained rather than requiring unforeseen leaps in intelligence.
Our Approach
We aim to build the global AI workforce by building generalist agents that live in high-fidelity virtual environments where they have access to the tools they need, followed by a global marketplace for hiring these AI workers salaried by the minute.
Reaching a true AI employee that is virtually indisinguishable from a remote human worker requires us to conquer three primary frontiers: planning, memory and always-on-behavior (AOB). We have already made significant advancements in planning which has allowed Kafka to achieve state-of-the-art performance on GAIA at a fraction of the cost without using reasoning models. We are currently hard at work on solving memory.