Principal Growth Marketing Engineer

Laurel•San Francisco, CA

3d•$180,000 - $200,000

About The Position

Laurel is on a mission to return time. As the leading AI Time platform for professional services firms, we’re transforming how organizations capture, analyze, and optimize their most valuable resource: time. Our proprietary machine learning technology automates work time capture and connects time data to business outcomes, enabling firms to increase profitability, improve client delivery, and make data-driven strategic decisions. We serve many of the world's largest accounting and law firms, including EY, Aprio, Crowell & Moring, and Frost Brown Todd, and process over 1 billion work activities annually that have never been collected and aggregated before Laurel’s AI Time platform. Our team comprises top talent in AI, product development, and engineering—innovative, humble, and forward-thinking professionals committed to redefining productivity in the knowledge economy. We're building solutions that empower workers to deliver twice the value in half the time, giving people more time to be creative and impactful. If you're passionate about transforming how people work and building a lasting company that explores the essence of time itself, we'd love to meet you. About the Role Reporting to the VP, Growth Marketing & Operations, you are the operational and technical engine behind our marketing data infrastructure, paid programs, and AI-powered campaign tooling. You build systems that make campaigns measurable, automations that make the team faster, and agents that make spend smarter. You own the website — the technical foundation and the instrumentation that make it fast, findable, and measurable. This is a hands-on technical role. You build, maintain, and optimize, and you own the numbers on everything you touch.

Requirements

10+ years in web development, marketing operations, growth marketing, or a technical digital marketing role in B2B
Deep marketing automation experience (HubSpot): workflows, lead scoring, lifecycle management, attribution, and reporting
Hands-on paid B2B channels (LinkedIn, Google): targeting, pacing, creative testing, and performance analysis
Hands-on web development: shipping production code, owning the deploy, and optimizing performance.
Experience building or working with AI agents or automation frameworks — comfortable with APIs, prompt engineering, or orchestration tools
Demonstrated SEO/AEO ownership — technical audits, IA and content strategy, and organic growth you can point to with numbers
Strong data instincts — you build clean tracking, trust the attribution, and make decisions from numbers

Nice To Haves

Experience marketing to professional services, legal, or financial enterprise buyers
SQL or Python fluency for self-serve data work
Experience with Google Ads Scripts, Performance Max, or campaign automation tools
Prior work with LLM-based agents or workflow orchestration platforms (n8n, Make, Zapier, LangChain)

Responsibilities

Own site technical health — Core Web Vitals, speed, accessibility, crawlability, redirects — and the standards agencies build against
Run technical SEO audits and resolve crawl and indexation issues as the site grows
Build the templates, modules, and tracking components that let the team ship without a developer
Own the analytics stack — GA4, GTM, Search Console — and the measurement plan behind it
Drive organic strategy for ICP — keyword and topic strategy, on-page, IA, and content briefs
Lead AI Engine Optimization (AEO) so Laurel surfaces in LLMs
Drive organic strategy for ICP — technical SEO, on-page, IA, and content briefs
Run technical audits and resolve crawl and indexation issues as the site grows
Build the structured data and content architecture that makes Laurel citable to LLM retrieval
Track AI-assisted visibility and the organic pipeline that follows
Own the HubSpot instance: workflows, lifecycle stages, lead scoring, list management, and campaign tracking infrastructure
Build and maintain contact database hygiene, segmentation logic, and attribution across all touchpoints
Configure UTM structures, form tracking, and pipeline reporting so every campaign ties back to revenue
Ensure data flow between HubSpot and CRM is accurate, reliable, and audit-ready
Execute and optimize paid LinkedIn campaigns: audience targeting, budget pacing, creative trafficking, and A/B testing
Build reporting frameworks that connect LinkedIn spend to pipeline contribution, not just clicks
Identify performance patterns in the data and act on them — audience refinement, bid adjustments, creative rotation
Establish and maintain campaign architecture so performance data is always trustworthy
Build and maintain an AI agent that manages Google Ads operations: keyword management, bid strategy, budget allocation, and anomaly detection
Orchestrate the agent across campaign types — search, display, retargeting — using performance signals to drive autonomous optimization decisions
Define the logic, guardrails, and escalation rules so the agent operates reliably without constant supervision
Continuously improve agent performance by feeding it better signals, tighter rules, and accurate data
Collaborate with the AI Engineering team to identify and implement AI-powered marketing workflows beyond Google Ads
Drive adoption of these workflows, ensuring solutions are effectively implemented, measured, and continuously improved
Build and maintain dashboards across HubSpot, LinkedIn, and Google Ads that provide unified view of pipeline contribution by channel
Own attribution modeling for paid channels — last touch, multi-touch, and assist credit
Surface actionable insights that drive budget allocation, campaign optimization, and growth strategy, and improve conversion rates across the buyer journey