GTM Engineer

Full Job Description

The world’s largest law firm won’t be a law firm. Join us in building it.

August allows law firms to compound their expertise by building an autonomous organization of AI agents that run the firm's knowledge work. We partner closely with our firms and grow alongside them through sharing revenue on our agents and equity in the firms we transform.

We believe that in five years, more than 95% of legal work will be concentrated among a select few elite law firms. The firms that get there will be the ones that rebuild how they deliver it. We're partnering with those firms and building the engine they run on to become the biggest legal service provider in the world.

We invest in partnerships, not just licenses. We sell finished legal work alongside our firms and take a share of what it earns. This enables them to scale their services and lets us grow along with it. That means we’re chasing the legal services market ($1T), which dwarfs the global legal tech market ($40b).

The problem is hard. An engine of agents sits underneath every matter we touch, connected to every step of a lawyer's workflow, in an industry where there is no margin for error. We’re challenged with building the perfectly accurate, infallibly secure, and yet all-powerful engine for legal work.

We're already live with several excellent firms and the early results are better than we expected. Lean team, in person, New York, backed by leading investors, growing fast.

Every role at August is a chance to remake an industry while the window is open.

Join us in building the autopilot for legal services

Today, legal work is done the way it has been done for a century — manually, by humans, in six-minute increments. Every contract drafted from scratch. Every memo researched line by line. Every matter running through layers of review that someone is paying for at hundreds of dollars an hour.

That is about to change. We believe that in five years, more than 80% of legal work will pass through a model before it ever reaches a human. The implication is not faster lawyers — it is a fundamentally different way that legal services get bought and procured.

Our mission is to make high-quality legal work accessible and affordable for everyone. We are going after the services spend, not the software spend — helping law firms restructure their delivery model around AI, and helping in-house teams do the same. One engine of agents and workflows underneath every matter we touch.

We are a lean, in-person based in New York City, backed by leading investors and growing fast. Every role at August is a chance to remake an industry while the window is open.

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 Do

Outbound 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

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