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AI Founding Engineer (w/ Strong Product & Frontend Experience)

Hybrid — San Francisco, NYC, Vancouver

Full-Time

Est. Fee

$7,500-$15,000

Salary Range

$100,000 – $150,000 per year (varies by market, e.g. SF vs Vancouver)

Contract

7.5% of Salary, 90 day guarantee

Job Details

Job Overview

As a Founding Engineer, you’ll spearhead the development of the core systems that power an emerging AI GTM and revenue intelligence platform — taking the product from 0 → reliable operation. You’ll transform messy, fragmented go-to-market data into robust, product-ready models that enable intelligent account prioritization, agentic workflows, and real-time decision-making. The company is positioning itself as a new challenger in the 6sense category, rethinking how GTM data platforms are built from the ground up. Experience at companies like 6sense, Demandbase, Clari, or others in the GTM data/revenue intelligence ecosystem is a major plus, and will help you hit the ground running. Compensation: $100,000 – $200,000 base salary + meaningful equity. Actual offers are benchmarked by experience and location — for example, Vancouver salaries are typically lower than those in SF or NYC, consistent with local market rates. This is an opportunity to join at the ground floor, own major architectural decisions, and shape a platform in a high-growth, competitive space.

Responsibilities

As a founding engineer you will own core systems end to end and ship V1s fast. You will turn messy GTM data into working product, instrument results, and iterate in tight build-measure-learn loops with Product and Sales.

Create the collective memory: Ingest and unify multi-source data into a multi-level context graph with strong tenant isolation.
Orchestrate agentic systems: Design planner and executor patterns, tools, and policies that transform context into actionable content and build lightweight evaluation harnesses.
Deliver where users work: Ship native surfaces and integrations within apps, chat, and GTM tools in collaboration with Product and Sales teams.
Prove outcomes: Define metrics such as tasks auto-completed and adoption rates, and wire observability for rapid ship-learn-iterate cycles.
Balance cost and reliability: Tune for accuracy, latency, and cost while implementing fallbacks and safeguards for real-world loads.

Qualifications

We’re looking for an owner-builder who can take a fuzzy problem from zero to one and then operate it reliably in production. You pair strong Python/backend fundamentals with practical product taste, sound data modeling, and the judgment to make trade-offs and ship.

4+ years of experience in building and owning backend or platform systems with measurable business impact.
Strong proficiency in Python and ability to establish cloud infrastructure and production services.
Experience in integrating messy, multi-source data into product-ready models with sound reliability, privacy, and multi-tenant boundaries.
Possess product thinking, a bias to ship, and comfort making decisions with approximately 70% of information.

Ideal Candidate

Owner-builder who loves turning fuzzy problems into shipped systems and measuring real customer impact.

Early engineer from an AI/data/infra or GTM-tooling startup; comfortable owning a platform surface and taking it from 0→1→reliable operation.
Strong backend in Python; has stood up cloud services (preferably AWS) and production pipelines; familiarity with FastAPI/GraphQL, Postgres or DynamoDB, Kubernetes, Pulumi, and event-driven patterns.
Experience with agentic/retrieval systems or graph-shaped context; has designed planner/executor loops, added evals/observability, and shipped iterative improvements.
Sound multi-tenant data modeling, privacy, reliability, and fallback instincts; clear communicator of trade-offs.
Product taste: partners with Product and Sales, writes lightweight design docs, and iterates quickly based on metrics.
Able to work hybrid 3 days/week from San Francisco, New York City, or Vancouver (or relocate on an agreed timeline).

The company is a new entrant in the same category as 6sense, competing in the emerging AI-powered GTM and revenue intelligence space. Candidates with prior experience at 6sense or with deep expertise in GTM data platforms, revenue intelligence, or account prioritization tools are highly attractive for this role.

Must-Have Requirements

4+ years building and owning backend/platform systems end-to-end
Has had experience at an early-stage, high-growth startup or has founded/built their own project.
Strong proficiency in Python
Experience with cloud infrastructure and production services
Experience with data integration and reliability management
Product-oriented thinking with a bias to ship
Has not applied directly to the company before.

Screening Questions

1. (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.

2. (Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.

3. What’s the most recent technology or skill you taught yourself outside of work requirements, and how did you apply it?

4. Describe a feature or system you built. What problem did it solve for users/the business, and what metrics improved?

5. What do you understand about Revic’s product and market? What questions do you have about our approach?

6. Why do you want to work at an early-stage startup? What does it take to work at an early-stage startup?

7. Hybrid location (KO): Which office can you work from 3 days/week — San Francisco, New York City, or Vancouver? If relocating, what’s the timeline?

8. Work authorization (KO): Do you currently have work authorization for that location (US or Canada) without sponsorship?

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