Tech Stack

Description

You will architect the commercial infrastructure for Hazel AI, building automated systems for sales, marketing, and data analytics to drive growth. This hybrid role involves designing the GTM tech stack, creating AI-powered workflows, and partnering with cross-functional teams to turn strategy into scalable technical solutions.

Requirements

• 2-4 years of experience in Product/GTM Engineering at a high-growth SaaS or fintech company.
• Demonstrated ability to write production-quality code in Python, TypeScript or JavaScript to build integrations, automation workflows, and data pipelines.
• Have built or prototyped AI-powered workflows using LLM APIs, Claude Code and/or OpenClaw.
• Hands-on experience with CRM platforms (HubSpot or Salesforce), marketing automation, and sales engagement tools (Outreach, Salesloft, Apollo, or similar).
• Strong SQL skills and comfort working with data warehouses (Snowflake, BigQuery, or Databricks) to build revenue dashboards and funnel analytics.
• Experience with data enrichment and orchestration tools (Clay, Clearbit, ZoomInfo, or similar) to build intelligent lead flows.
• A systems-thinker who can design scalable GTM architecture, not just patch point solutions.
• Strong cross-functional communication skills – you’ll translate between business stakeholders and technical systems regularly.
• Comfort with ambiguity and early-stage pace – you move fast, prioritize ruthlessly, and iterate on the fly.

Responsibilities

• Design, build, and own Hazel’s GTM tech stack – including CRM (HubSpot/Salesforce), marketing automation, data enrichment, and outbound sequencing tools.
• Build automated workflows and AI-powered systems to support lead scoring, lifecycle marketing, outbound prospecting, and account-based motion.
• Write Python and/or JavaScript to connect data sources, automate enrichment pipelines, and extend CRM capabilities through APIs and custom integrations.
• Instrument the full funnel – from top-of-funnel awareness through activation and expansion – to surface actionable insights and revenue attribution to GTM leadership.
• Partner with Sales, Marketing, and Product to translate business needs into scalable technical solutions; own delivery end-to-end.
• Build and maintain a clean, reliable data foundation in our revenue data warehouse, enabling accurate forecasting and pipeline analytics.
• Evaluate and implement AI tools (e.g., Clay, Apollo, Instantly, and emerging LLM-based GTM tools) to amplify rep productivity and pipeline quality.
• Reduce manual ops overhead by automating repetitive GTM tasks so the team can focus on high-leverage activities.
• Willingness and comfort serving as technical support for AEs on sales calls.