GTM Automation Engineer

Crexi•Los Angeles, CA

2d•Hybrid

About The Position

Crexi is hiring a GTM Automation Engineer to build and operate AI-driven workflows that help go-to-market teams engage brokers, investors, and owners with less manual effort. The role converts marketplace activity, CRM records, enrichment data, and conversation data into useful signals and automations for sales and marketing teams. The engineer takes defined projects from prototype through production across Crexi’s sales, marketing, and revenue technology stack, partners closely with the teams using the tools, and is accountable for measurable outcomes such as meetings, pipeline, revenue, and time saved. The role includes automating prospect research and outreach preparation; building data sourcing and enrichment pipelines; creating signals, scores, and alerts; integrating AI and agent workflows with GTM systems; measuring business impact; and gathering feedback by working directly with SDRs, Account Executives, and Marketing. It also owns production reliability and quality, follows data governance, security, privacy, and outreach compliance requirements, evaluates build-versus-buy options, and documents systems and operating procedures. The position is hybrid in Los Angeles. Crexi describes itself as a rapidly scaling commercial real estate marketplace using AI to modernize the industry.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
At least 3 years of experience in GTM engineering, growth or revenue operations, software or data engineering, or a similar technical role supporting or closely partnering with a revenue team.
Demonstrated cross-functional work with teams such as Sales, Marketing, Revenue Operations, and Engineering, delivering measurable business results such as pipeline, conversion, or productivity gains.
Hands-on experience shipping LLM-based applications or automations to production users.
Working knowledge of Salesforce or HubSpot and tools such as Outreach and Clay, including their data structures and APIs.
Ability to build in Python or TypeScript and deliver version-controlled, tested integrations.
Experience building with large language models, including thoughtful use of prompts, context, tools, and evaluation, and judgment about when AI is not the right solution.
Comfort with SQL and messy CRM and third-party data, including deduplication and account matching.
Understanding of GTM workflows, including prospecting, lead routing, and pipeline management, and familiarity with the work of an SDR.
Ability to take projects from idea to completion within priorities set by Revenue Operations and GTM leaders, and to explain technical tradeoffs clearly to non-technical partners.
Use of AI coding assistants such as Claude Code or Cursor while maintaining the quality of shipped work.

Nice To Haves

Hands-on experience with Clay, Search API, Gong, or Qualified, and sourcing and structuring external data at scale.
Experience with Snowflake or dbt, or syncing warehouse data back into a CRM.
Background in experimentation or analytics, or prior work supporting SDR or outbound sales teams.
Experience in commercial real estate, marketplaces, or B2B SaaS.
A repository, portfolio, or short demo showcasing shipped LLM-based applications or automations.

Responsibilities

Build and own automated workflows for account research, prospect prioritization, and outreach drafting, with human review for customer-facing material.
Develop and maintain data sourcing and enrichment pipelines that deliver clean, deduplicated records to Salesforce, HubSpot, and downstream sales tools, while respecting API limits.
Combine marketplace activity, CRM history, enrichment, and conversation data into signals, scores, and Slack alerts that guide prospect engagement and manager coaching.
Integrate LLMs and agent workflows across the GTM stack, including Salesforce, HubSpot, Outreach, Gong, Qualified, Slack, and Snowflake; use simpler rules where they are more effective.
Instrument new builds and report impact on meetings booked, pipeline created, conversion rates, and representative time saved, partnering with Revenue Operations on baselines and attribution.
Spend regular time with SDRs, Account Executives, and Marketing, including shadowing prospecting and reviewing Gong calls, to identify problems, define requirements, and improve tools based on feedback.
Maintain production automation reliability through monitoring, alerting, retries, and evaluation sets for LLM outputs; diagnose failures, data issues, and model regressions, and escalate broader-impact issues to Revenue Operations.
Follow company data governance, security, and privacy standards, including applicable outreach consent and opt-out requirements and responsible handling of customer data shared with AI vendors.
Evaluate GTM and AI tools using working prototypes, recommend whether to build, buy, or extend, and help maximize the value of native AI features in existing licensed tools.
Document systems, data flows, prompts, and runbooks for Revenue Operations and GTM leaders.