Senior Full Stack Engineer, AI & Growth Systems

Eve’s Go-To-Market team — growth, marketing, sales, and RevOps — moves fast and runs on software, and we’re building a lot of it. As a Senior Software Engineer on this team, you’ll own large parts of that software: internal tools, integrations, GTM data and automation systems, and the web platform — the systems that turn manual GTM work into something repeatable and reliable.

This is full-stack product engineering, embedded in Go-To-Market. The work is broad and the pipeline is long: a web platform marketers can publish to without an engineer, internal tools for sales and RevOps, integrations with the systems the business runs on, and data and automation workflows — increasingly AI-assisted — that replace work people do by hand today. The web platform was our first project; it’s one surface among many coming, and you’ll have a real hand in deciding how the rest get built.

You’ll be the second engineer on this surface, working as a true peer to our current engineer — tag-teaming the big ambiguous projects and running whole workstreams independently. You’ll take a vague business problem — “we can’t ship site changes without an engineer,” “this lead-routing breaks silently,” “we do this enrichment by hand every week” — find the real requirements, decide what (and what not) to build, and own it through to production. The highest-leverage version of this job isn’t shipping the next one-off; it’s building the reusable primitives that make the next ten GTM projects faster.

This is not a research role, a pure-infrastructure role, or a “hardest technical problem” role. The hard part here is usually the messy business context, the reliability bar, and the breadth — not algorithmic novelty. We want a pragmatic, execution-oriented engineer who ships and raises everyone’s throughput without adding management load.

• End-to-end ownership. Own workstreams across frontend, backend, APIs, and data — and run several in parallel — from ambiguous business problem to shipped, monitored, maintained software.
• Internal tools, integrations, and GTM systems. Connect CRMs, marketing automation, data warehouses, and third-party APIs into workflows the business can trust, including AI-assisted workflows where they earn their place.
• Reusable primitives over one-offs. When the same problem shows up repeatedly, build the ingestion, storage, generation, evaluation, and observability pieces that unlock the next ten workflows.
• The web platform. Own and evolve our content-driven site as one of several surfaces — fast, accessible, and safe for non-engineers to publish to.
• Reliability. Webhooks, data syncs, and production errors are yours; you add the monitoring, validation, and runbooks that catch problems before stakeholders do.
• Working with the business. Partner directly with growth, sales, and RevOps — do the discovery, translate messy workflows into software, and measure whether it actually helped.
• Raising the bar. Lift the team through code review, reusable patterns, and good “do we even build this?” judgment — including saying no when that’s the right answer

• Bachelor's degree in Computer Science or equivalent.
• Business-critical production experience. You’ve built and owned software real users or real revenue depended on, well past launch.
• Roughly 6+ years of professional experience, though we weight ownership and judgment over tenure.
• Frontend strength with full-stack depth. You excel in modern web stacks (React, TypeScript, etc.) and own frontend-heavy projects end-to-end—but you're comfortable diving into backend, APIs, and databases when needed for integrations and infrastructure. You can take an ambiguous problem to production across the stack without it being pre-scoped. We're not dogmatic about specific languages, but web platform excellence is the priority.
• Internal tools for non-engineering teams that were genuinely adopted, with discovery done before building.
• Fluency with AI-assisted development — orchestrating tools like Claude Code, Cursor, or Codex as a real part of your workflow, with strong opinions on task decomposition, context-setting, review, and the tests and guardrails that keep AI-generated work from degrading quality. It’s central to how this team works.
• Applied LLM, agent, or automation systems taken well past prototype, with real attention to evals, observability, and failure modes.
• Strong debugging and reliability instincts. You chase problems to their actual root cause through frontends, APIs, webhooks, data syncs, and production logs — and you build the guardrails that keep the same class of bug from recurring.
• Product and business judgment. You understand why you’re building something, negotiate scope and tradeoffs directly with non-engineers, choose simple durable solutions under ambiguity, and push back when the right answer is “don’t build this.”
• Independent ownership. You can take a fuzzy workstream and run it to production with minimal supervision, while keeping others unblocked.
• Low-ego, high-collaboration leadership. You communicate clearly in writing and in person, mentor by example, and make the people around you more effective

• A modern TypeScript web stack and/or headless/CMS-backed sites (e.g. Astro, Next, SvelteKit; Sanity, Contentful, or similar), including content models that let non-engineers publish safely.
• GTM and data systems depth: Familiarity with HubSpot, Salesforce, Snowflake, Segment, Clay, Apollo, or equivalents — plus fluent SQL for inspecting and validating data.
• A track record integrating messy third-party APIs reliably — attribution, identity resolution, lead routing, enrichment, scoring, sync-failure handling.
• Growth, activation, or web-platform engineering — experimentation, conversion, performance, SEO, and the metrics and guardrails that go with them.
• Experience in legal, financial services, healthcare, or another domain where correctness matters and outputs must be defensibly right