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August Law

AI-powered legal assistant automating document-intensive tasks

GTM Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • Have 2–4+ years of software engineering experience at SDE2 or SDE3 level.
  • Have strong programming skills in Python, JavaScript/Node.js, and SQL.
  • Have expertise integrating REST APIs, webhooks, OAuth, rate limiting, and error handling.
  • Have experience at a top-tier technology company or similar organization.
  • Understand data engineering fundamentals, including ETL pipelines, data transformations, and analytics instrumentation.
  • Be able to design scalable, maintainable infrastructure.
  • Have experience with A/B testing, statistical analysis, and systematic optimization.
  • Have a degree from a top engineering institution such as IIT, BITS Pilani, NIT, IISc, or equivalent.

Responsibilities

  • 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 email deliverability through SPF/DKIM/DMARC configuration, domain warmup automation, and bounce handling.
  • Build LinkedIn prospecting automation for connection requests, message sequences, and engagement tracking.
  • Design rate limiting and anti-detection systems to maintain account health at scale.
  • Implement targeting optimization by testing job titles, seniority, industries, and company sizes.
  • Build an analytics pipeline to track connection rates, response rates, and meeting bookings by segment.
  • Develop session management and proxy rotation infrastructure.
  • Automate technical SEO, including schema markup generation, sitemap updates, and crawl error monitoring.
  • Build content optimization pipelines for keyword research automation, content gap analysis, and meta tag generation.
  • Integrate the Google Search Console API for ranking tracking and organic traffic attribution.
  • Design an experiment framework for title patterns, URL structures, and internal linking strategies.
  • Implement performance monitoring through Core Web Vitals tracking and page speed optimization automation.
  • Build a referral tracking system with unique link generation, attribution logic, and conversion tracking.
  • Design viral loop mechanics for referral incentive automation, reward distribution, and fraud detection.
  • Implement an analytics dashboard for viral coefficient tracking, referral funnel analysis, and cohort performance.
  • Integrate with CRM and billing systems for automated reward fulfillment.
  • Instrument event tracking across acquisition channels using PostHog.
  • Build a data warehouse ETL process aggregating data from Clay, HubSpot, Amplemarket, Google Ads, and LinkedIn.
  • Design an A/B testing framework with Statsig for experiment allocation, variant tracking, and statistical analysis.
  • Develop real-time dashboards for outbound performance, SEO rankings, referral metrics, and conversion funnels.
  • Build an attribution modeling system for multi-touch attribution, CAC by channel, and LTV cohort analysis.
  • Integrate the Google Ads API for programmatic campaign management.
  • Build automated bidding systems for budget allocation, CPC optimization, and keyword performance monitoring.
  • Implement an ad variant testing framework for systematic rotation of ad copy, landing pages, and targeting parameters.
  • Develop conversion tracking and ROI analysis pipelines.
  • Build HubSpot API integrations for bidirectional sync with GTM tools, automated lead scoring, and workflow triggers.
  • Design data quality systems for deduplication, enrichment automation, and field validation.
  • Implement sales analytics for pipeline visibility, lead source attribution, conversion rates, and deal velocity tracking.
  • Build internal sales operations tools, including custom dashboards, reporting automation, and forecast modeling.
  • Handle rate limits, retries, error handling, and webhook reliability across five or more third-party platforms.
  • Build session management, behavior randomization, and proxy rotation for LinkedIn automation.
  • Design a statistically sound A/B testing framework with proper randomization and significance testing.
  • Build reliable ETL data pipelines from GTM tools to an analytics warehouse and handle schema changes and data quality.
  • Improve open rates, response rates, and conversion rates through automated experimentation.
  • Build dashboards with under one-minute latency for sales and marketing operations visibility.
  • Build a full analytics pipeline from GTM tools to the warehouse and implement outbound and LinkedIn experimentation infrastructure during the first one to two months.
  • Create dashboards for key outbound performance, SEO ranking, and referral funnel metrics during the first one to two months.
  • Run five to ten experiments per week across outbound, LinkedIn, and SEO; identify and scale top-performing variants; and reduce manual work through automation during months three to four.
  • Double outbound capacity through automation, launch a fully tracked referral platform, build predictive models for lead scoring and channel allocation, and automate SEO optimizations based on ranking data during months five to six.

Desired Qualifications

  • Experience with GTM automation platforms such as Clay, Amplemarket, and Apollo, including their APIs.
  • Knowledge of LinkedIn APIs, scraping techniques, or anti-detection systems.
  • Familiarity with SEO tools and APIs such as Ahrefs, SEMrush, and Google Search Console.
  • Hands-on experience with analytics platforms such as PostHog, Mixpanel, Amplitude, and Statsig.
  • Experience with the 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 at a pre-Series B company.

About the Company

August Law

AI-powered legal assistant automating document-intensive tasks

August Law builds AI tools for the legal sector, with Oliver as its flagship AI-powered assistant that automates document-heavy tasks like research, review, and drafting. Oliver uses a modular agent framework that mimics attorney decision-making, connects to a firm’s internal data sources and external databases, and provides real-time source citations with deployment options on a firm’s network or a private cloud. It differentiates itself by targeting underserved midsize law firms, offering configurable AI workflows aligned with a firm’s playbooks, strong auditability, and flexible deployment to meet data security and residency requirements. The company aims to boost efficiency in tasks such as due diligence, contract review, and discovery, while enabling new fee structures and expanding its market presence globally, including in India.

Company size
11-50
Company stage
Early VC
Total funding
$7M
Headquarters
New York City, New York
Founded
2023

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