GTM Engineer
SageOx
GTM Engineer
SageOx
Shared memory for human–AI coding teams
This role is based in Seattle, Washington (open to considering San Francisco-based candidates)
Teams increasingly build through prompts, coding agents, assistants, meetings, and automations — and the context across those surfaces fragments quickly. SageOx is the hivemind for human-agent teams: a new product and a new category to explain. That takes someone who can build the market alongside the product, not operate a mature acquisition channel. We are looking to onboard a superstar who owns the loop from customer conversation → experiment → measured learning, and runs it every week.
This is an early, hands-on position with meaningful influence over positioning, distribution, integrations, and the product roadmap. You’ll work closely with the founders on the narrative as you learn from customers and the ecosystem what resonates.
Your mission is to make SageOx known by customers. Build and run the demand engine: content, channels, community, outbound, experiments, and the tooling underneath them.
We're looking for a GTM Engineer who loves building and lives on the cutting edge of AI. This role doesn't just tell the story, it engineers the machine that spreads it.
This role speaks as SageOx. Whoever holds it becomes an extension of the founding team in public — which is why deep alignment with SageOx's mission and culture is a hard requirement, not a preference. The center of gravity matters: this person promotes SageOx, not themselves. Their skill will make them visible: that's a byproduct we're glad about, but it’s not the goal. The audience they build belongs to the company. If your ambition is to make a company famous and create great value in the process, this is one of the best seats in the ecosystem to do it from.
This is a high-impact, high-agency role: as our first hire in this area, you'll wear a lot of hats while setting the strategy. You’ll have a high degree of autonomy to work with any function, with any support from the team you need. You'll work directly with leadership to find the highest-leverage problems, then own them end to end.
Learn — own the customer and market loop
Talk directly with founders, engineers, product teams, and other agent-heavy builders to understand where context is lost and what they've already tried.
Map the territory around the ideal customer: the tools, communities, search terms, adjacent products, and workflows that already surround them.
Be the tip of the spear for market feedback. This person spends their days where the conversation happens — reading, commenting, engaging on social media and in communities. Surface important trends and developments to the team; relay the feedback that matters from prospects and ecosystem players. Outside-in signal is a deliverable of this role, not a byproduct.
Create a steady customer-learning cadence and make the findings legible to product and engineering.
Evangelize — turn learning into voice
Run the content machinery around SageOx: turn internal insights and learnings, customer stories, and shipped features into X threads, posts, short video, and longer pieces: on cadence, every week.
Turn customer conversations into precise positioning inputs, demos, tutorials, comparison pages, workflow documentation, case studies, and product feedback.
Be the team's external voice engine. Many great insights and ideas originate inside the team, as we experiment with internal tooling and practices. This role turns those raw ideas into public voice.
Amplify the founders directly: identify the highest-impact platforms, podcasts, and moments for the founders to show up, get them there, and connect them with the audiences that matter.
Run community marketing: launches, dev-influencer collabs, and hackathons — measured in signups flowing in. Own event presence. Help develop SageOx's presence across the Seattle and San Francisco builder communities.
Dogfood SageOx daily and evangelize from lived use, not talking points.
Build — engineer the machine
Build AI-powered tools and agents across the business: prospecting automation, lead scoring and enrichment, customer-facing utilities and demos.
Build lightweight technical assets: integrations, MCP-based workflows, public utilities, templates, and examples that pull the ecosystem toward SageOx.
Build the outbound engine: find teams building agents, surface champions inside companies already using us, and automate personalized outreach.
Automate the GTM stack: wire together our CRM, data sources, and onboarding funnel so the machine runs itself.
Build repeatable agent-assisted workflows for research, monitoring, drafting, outreach, and reporting, without outsourcing judgment to the agents.
Experiment — measure, decide, systematize
Run small distribution experiments across developer communities, events, content, integrations, marketplaces, partnerships, and targeted outbound. Own the process end to end: form a hypothesis, build the thing, ship it, measure it, and kill it or scale it.
Instrument everything: define useful activation and conversion signals, and decide what to stop, improve, or scale.
Turn wins into playbooks: find the bottleneck, wire up the automation that removes it, and make every winning play repeatable.
Numbers, not vibes; traction, not vanity. The metrics that count are meaningful company traction: qualified signups/trials sourced per week, engaged conversations that convert into customers, experiments run per month with documented learnings (a kill is a result). Follower counts and impressions are not the scoreboard; a smaller audience that converts beats a big one that scrolls past. Audience growth matters only on channels that demonstrably convert.
7 days: publishing on cadence from founder brain-dumps with a light review pass; first channel experiments live with baselines.
14 days: ~3 posts + 1 long piece weekly, sustained; visible and targeted social media engagement daily; at least two channel experiments concluded with keep/kill decisions; first GTM automation prototyped; customer-learning cadence established and legible to the team; first measurable inbound signups attributed to content.
2 months: the demand engine runs without founder production time; outbound engine v1 live (target lists, champion surfacing, personalized outreach automated); a repeatable experiment playbook exists; inbound is a visible share of new trials.
Ships useful things instead of producing strategy decks without execution.
Moves from an ambiguous customer problem to a testable hypothesis to a finished experiment.
Balances speed with taste. The goal is not maximum output; it is impactful output for the right audience. In the age of AI slop, that often entails editing and synthesizing, rather than producing more.
Comfortable talking to customers, asking sharp questions — and changing direction when evidence contradicts the original idea.
Finds a distribution path rather than waiting to inherit one.
Works well with founders and team, communicates progress without excessive process, and makes the next decision clearer.
We don't care which door you came through — engineering, solutions engineering, technical marketing, or growth. We care that you build relentlessly and understand what AI makes possible right now.
2–7 years of experience in software engineering, solutions engineering, technical marketing, or growth — the background matters less than the builder instinct and the willingness to experiment until you've hit the target.
Mission & culture alignment (non-negotiable): believes in what SageOx is building — the hivemind for human-agent teams — enough to represent it as their own. Company-first orientation.
A track record of shipping: core or side projects, internal tools, hackathon wins, open source — show us things you've built. Has personally grown an audience, a funnel, or a channel somewhere.
Deep, hands-on fluency with AI, daily (non-negotiable): you've built with the latest AI models and agent frameworks, have opinions about them, and use AI to scale your own work. The pitch is only credible from a practitioner.
Technical enough to build the machine: works comfortably with AI tools and AI coding agents, MCP, integrations, analytics, and modern AI development workflows.
Experiment-minded: thinks creatively, makes many parallel bets, and picks the winners; can talk in hypotheses, baselines, and results.
Deep customer empathy: genuinely wants to understand and solve customer problems and orients toward finding those customers.
Communicates clearly — via writing, video, or practical projects built with SageOx itself; explains a technical product through concrete workflows rather than category jargon.
Strong sense of ownership: owns outcomes, not tasks, and makes things happen with limited resources; a great sense of direction and prioritization amid the ambiguity of an early-stage startup.
Cultural fit: ships fast, tolerates public failure, measures, iterates; needs direction, not supervision; embraces transparency; focused on making the team win.
Connected to the builder scene - in San Francisco, Seattle, and online.
Same as every role here. In person, five days a week, in Seattle. We move fast and the work benefits enormously from being in the room.
One narrow exception: Bay Area-based candidates we can get to Seattle at least two weeks a month, through end of 2026.
No traditional interviews. We'll clear an initial assessment and invite you to a work trial: 3–5 days in Seattle, working on something real alongside the team, the way the team actually works. Most of what matters shows up there faster than any interview loop could reveal.
Before applying, please learn more about our work trials.
Ajit wrote up why we hire this way: Read the post
$15M seed led by Canaan, with A.Capital, Pioneer Square Labs, and Founders' Co-op. Founded by Ajit Banerjee (AWS EC2/EBS, XetHub → Hugging Face), Ryan Snodgrass (early Amazon, Kindle/AWS-scale cloud systems), and Milkana Brace (EVP of Product at Remitly). Small on purpose. More about the team →
Competitive salary and meaningful equity. We'll talk specifics once we know it's a real mutual fit.
We're not working with recruiters or recruiting agencies/consultants at this time — direct applications only, please.
SageOx builds agentic context infrastructure to keep AI coding agents and human teams aligned by creating a shared memory of decisions, constraints, and reasoning from discussions and agent sessions. It operates through four components: Team Context to define governing principles, Ledger of Work to record reasoning and intent, the Ox CLI to prime agent sessions with shared context, and a web app to search and navigate the history, linking code commits to original intent. The platform differentiates itself by enabling multiplayer by default, so every human and AI agent draws from a versioned, common context instead of working in isolated sessions, which helps prevent architectural drift. Its goal is to prevent context loss and rework in AI-assisted software development, delivering a SaaS product for AI-native teams (initially focusing on Claude/Anthropic models) to support aligned human-agent collaboration throughout the software development lifecycle.
Explore more opportunities at SageOx