Full-Stack GTM Engineer

Posted 2 Days Ago
Hiring Remotely in New York, NY
Remote or Hybrid
Mid level
Legal Tech • Software
Configurable legal AI platform built for midsized firms.
The Role
Build and optimize go-to-market technical infrastructure: multi-channel prospecting, LinkedIn automation, SEO pipelines, referral tracking, analytics and experiment frameworks, API integrations, ETL/data warehouse, and real-time dashboards to drive and measure customer acquisition.
Summary Generated by Built In

At August, we’re building AI designed for one thing: helping law firms practice better. Unlike tools built for the AmLaw 100, our focus is on midsized firms — where efficiency, client service, and competitive advantage matter most.

Our platform helps lawyers draft, review, and analyze documents at scale, turning what used to take hours into minutes. We’re trusted by forward-thinking firms across the U.S., Australia, and Asia, and backed by leading investors (NEA, Pear VC, Stanford Law) to grow globally.

We move quickly, learn directly from clients, and believe that AI is transforming the practice of law.

THE ROLE

We're looking for a software engineer to build and optimize the technical infrastructure that powers customer acquisition. You'll design data pipelines, integrate third-party APIs, build experiment frameworks, and systematically improve performance across our outbound, SEO, and automation systems.

This is systems engineering applied to go-to-market. You'll write code, design architectures, instrument analytics, and run optimization experiments—the same technical work as any backend or infra engineer, just applied to acquisition systems instead of product features.

WHAT YOU'LL DOOutbound Automation Systems
  • Design and implement multi-channel prospecting pipelines using Clay, Amplemarket, and Apollo APIs

  • Build experiment frameworks to A/B test email sequences, subject lines, send times, and message variants

  • Develop lead enrichment and scoring systems with automated data quality checks

  • Implement webhook-based response detection and automated routing logic

  • Optimize deliverability: SPF/DKIM/DMARC configuration, domain warmup automation, bounce handling

LinkedIn Automation Infrastructure
  • Build LinkedIn prospecting automation: connection requests, message sequences, engagement tracking

  • Design rate limiting and anti-detection systems to maintain account health at scale

  • Implement targeting optimization: systematic testing of job titles, seniority, industries, company sizes

  • Build analytics pipeline to track connection rates, response rates, meeting bookings by segment

  • Develop session management and proxy rotation infrastructure

SEO Infrastructure & Optimization
  • Automate technical SEO: schema markup generation, sitemap updates, crawl error monitoring

  • Build content optimization pipelines: keyword research automation, content gap analysis, meta tag generation

  • Integrate Google Search Console API for ranking tracking and organic traffic attribution

  • Design experiment framework for title patterns, URL structures, internal linking strategies

  • Implement performance monitoring: Core Web Vitals tracking, page speed optimization automation

Referral Platform Engineering
  • Build referral tracking system: unique link generation, attribution logic, conversion tracking

  • Design viral loop mechanics: referral incentive automation, reward distribution, fraud detection

  • Implement analytics dashboard: viral coefficient tracking, referral funnel analysis, cohort performance

  • Integrate with CRM and billing systems for automated reward fulfillment

Analytics & Experimentation Infrastructure
  • Instrument event tracking across all acquisition channels using PostHog

  • Build data warehouse ETL: aggregate data from Clay, HubSpot, Amplemarket, Google Ads, LinkedIn

  • Design A/B testing framework with Statsig: experiment allocation, variant tracking, statistical analysis

  • Develop real-time dashboards for outbound performance, SEO rankings, referral metrics, conversion funnels

  • Build attribution modeling system: multi-touch attribution, CAC by channel, LTV cohort analysis

Google Ads Optimization
  • Integrate Google Ads API for programmatic campaign management

  • Build automated bidding systems: budget allocation, CPC optimization, keyword performance monitoring

  • Implement ad variant testing framework: systematic rotation of ad copy, landing pages, targeting parameters

  • Develop conversion tracking and ROI analysis pipelines

CRM & Sales Operations Automation
  • Build HubSpot API integrations: bidirectional sync with GTM tools, automated lead scoring, workflow triggers

  • Design data quality systems: deduplication logic, enrichment automation, field validation

  • Implement sales analytics: pipeline visibility, lead source attribution, conversion rates, deal velocity tracking

  • Build internal tools for sales ops: custom dashboards, reporting automation, forecast modeling

REQUIREMENTS
  • 2-4+ years of software engineering experience at SDE2 or SDE3 level

  • Strong programming skills: Python, JavaScript/Node.js, SQL

  • API integration expertise: REST APIs, webhooks, OAuth, rate limiting, error handling

  • Experience at a top-tier technology company (e.g., Amazon, Flipkart, Zomato, PhonePe, Razorpay, Setu, Uber, Google, Meta, D.E. Shaw, or similar)

  • Data engineering fundamentals: ETL pipelines, data transformations, analytics instrumentation

  • Systems thinking: Design scalable, maintainable infrastructure

  • Experimentation mindset: A/B testing, statistical analysis, systematic optimization

  • Degree from a top engineering institution (IIT, BITS Pilani, NIT, IISc, or equivalent)

BONUS POINTS
  • Experience with GTM automation platforms (Clay, Amplemarket, Apollo, HubSpot APIs)

  • Knowledge of LinkedIn APIs, scraping techniques, or anti-detection systems

  • Familiarity with SEO tools and APIs (Ahrefs, SEMrush, Google Search Console)

  • Hands-on with analytics platforms (PostHog, Mixpanel, Amplitude, Statsig)

  • Experience with Google Ads API or programmatic advertising systems

  • Background in data engineering, analytics infrastructure, or experimentation platforms

  • Prior work on referral systems, viral loops, or growth automation

  • Startup experience (especially pre-Series B)

TECHNICAL CHALLENGES
  • API integration at scale: Handle rate limits, retries, error handling, webhook reliability across 5+ third-party platforms

  • Anti-detection systems: Build session management, behavior randomization, proxy rotation for LinkedIn automation

  • Experiment infrastructure: Design statistically sound A/B testing framework with proper randomization and significance testing

  • Data pipeline engineering: Build reliable ETL from GTM tools to analytics warehouse, handle schema changes and data quality

  • Performance optimization: Systematically improve metrics (open rates, response rates, conversion rates) through automated experimentation

  • Real-time analytics: Build dashboards with <1min latency for sales and marketing ops visibility

WHAT SUCCESS LOOKS LIKE

Month 1-2: Infrastructure & instrumentation

  • Build full analytics pipeline from GTM tools to warehouse

  • Implement experiment framework for outbound and LinkedIn

  • Create dashboards for all key metrics (outbound performance, SEO rankings, referral funnel)

Month 3-4: Optimization velocity

  • Run 5-10 experiments per week across outbound, LinkedIn, SEO

  • Identify top-performing variants and scale them

  • Reduce manual work by 50% through automation

Month 5-6: Scale & predictive systems

  • Double outbound capacity through automation improvements

  • Launch referral platform with full tracking infrastructure

  • Build predictive models for lead scoring and channel allocation

  • Automate SEO optimizations based on ranking data

WHY THIS ROLE IS DIFFERENT

Most engineers build product features. You'll build the systems that acquire customers.

Same technical work—API integrations, data pipelines, experiment frameworks, performance optimization—but applied to acquisition instead of product. The code you write directly impacts revenue.

If you're an engineer who wants to:

  • See immediate business impact from your code

  • Work on diverse technical challenges (APIs, data pipelines, ML, automation)

  • Own entire systems end-to-end

  • Run experiments and optimize performance systematically

...this role is for you.

Why Join August
  • Founding Impact: Shape not just your role but the company.

  • Uncapped Upside: Competitive base + commission, early equity ownership.

  • Top-tier Team: Work alongside people who move fast, think clearly, and care deeply.

  • Category-Defining Work: Help build the first true AI agents for the legal profession.

  • Fast Growth: Scale your career as we scale the company.

  • Exceptional Early Traction: >4x revenue growth in the past four months.

  • Global Reach: Our clients span 4 continents and use August in multiple languages and jurisdictions

  • Frontier of Applied AI: August has access to proprietary data inaccessible to foundation model providers. We build agents to automate all challenging knowledge work.

  • Strategic investors: Backed by NEA and exceptional seed investors Pear VC and Afore Capital, August has the capital to execute

Top Skills

Python,Javascript,Node.Js,Sql,Rest Apis,Webhooks,Oauth,Clay,Amplemarket,Apollo,Hubspot,Posthog,Statsig,Google Ads Api,Google Search Console Api,Linkedin Api,Ahrefs,Semrush,Mixpanel,Amplitude,Spf,Dkim,Dmarc,Proxy Rotation,Scraping,Etl,Data Warehouse
Am I A Good Fit?
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The Company
HQ: New York, NY
15 Employees
Year Founded: 2024

What We Do

Our purpose is to bring this best-in-class legal AI tool for mid-sized law firms.

We're building Legal AI tailored to level the playing field for mid-sized firms, specifically configured to their type of work. Our platform is customized to each firms unique precedents and facts, matching internal style, while offering supporting with onboarding and adoption.

We're serving clients across four continents and backed by NEA, Pear VC, Stanford Law School and other incredible partners. To learn more, connect with us and reach out to [email protected]

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