Go-To-Market Engineer.

About ReBizReBiz is a monitoring and analytics company for multi-unit retailers. We turn the existing camera systemsand operational data in our customers' locations into verified daily evidence, from the individual rep upthrough the store, district, region and enterprise.Our go-to-market team runs AI-first. Skills, agents and workflows are the operating layer for how wemarket, sell and support customers. This role builds and maintains that layer.The roleYou own the AI workflows that marketing, sales, customer success, product and operations run on. Youtake a manual GTM process, turn it into an agentic workflow, prove it works and keep it working.Success is measured in faster lead response, more qualified pipeline per rep and hours of manual workremoved.This is a hands-on individual contributor role for an engineer who has already shipped agentic workflowsinto daily use. You report to the VP of Marketing and work directly with ReBiz executives.We build in Claude today. Everything you build should move to another model with minimal rework, somodel choice, prompts and brand context stay swappable inputs.What you'll doMarketing: inbound, ABM and content

• Own the systems behind speed-to-lead. Build automations that route, score and respond toinbound leads in minutes.
• Deploy lead-qualification, chat and form-follow-up agents that work the top of the funnelaround the clock.
• Build enrichment workflows that combine firmographic, technographic and behavioral signalsinto account scores and target lists for ABM and paid.
• Automate content and SEO operations, from production support to on-page optimization andperformance tracking.Sales: outbound and pipeline
• Build agents that research accounts, build lists and draft personalized outreach for reps.
• Design sequencing workflows that tune timing, cadence and messaging on engagement data.
• Mine call recordings and CRM activity for buying signals, risk flags and next-best-actionrecommendations.
• Flag stale deals, missing data and forecast risk early.Customer success, product and operations
• Surface account health and renewal risk from CRM, support and usage data.
• Turn customer calls and feedback into structured input for product.
• Automate recurring reporting and internal operations work.Platform, data and integrations
• Build custom MCP servers and API integrations that connect workflows to the systems our teamsalready use, including HubSpot, Google Workspace and internal data sources.
• Write custom code against third-party APIs, including rate-limit handling, retries, pagination andbatching.
• Set up and maintain the data warehouse our GTM workflows read from and write to, on aplatform such as Snowflake, Databricks or Google BigQuery.
• Keep lead, account and deal data accurate at every handoff between CRM, marketingautomation, enrichment and intent sources.
• Keep every workflow modular. One skill does one job well and chains with others. QA and guardrails
• Put an eval behind every deployed system. Measure lead-scoring accuracy, routing correctness,outreach quality and call-summary accuracy against human baselines.
• Require human review for anything customer-facing or rep-facing, with logging and a rollbackpath.
• Track cost, latency and failure rates. Fix regressions when a model or prompt changes.Partner, coach and document
• Work with executives and team leads to find the manual work worth automating, then rank it byrevenue impact and hours saved.
• Run fast experiments, track results and keep what moves the number.
• Coach non-technical teammates until the workflow is the default way the work gets done, thenhand matured systems to the teams that own them.
• Maintain a versioned prompt and skill library with documented, reusable templates.
• Report monthly on what shipped, what it saved and what comes next.What you bring
• A software engineering background: a computer science degree or equivalent, plus experienceshipping production code in Python or TypeScript and working SQL.
• 2+ years of hands-on AI experience building with LLMs.
• 1+ year creating, deploying and QA-ing agentic workflows that people use in their daily work.
• Strong working knowledge of Claude, including Claude Code, skills, subagents and tool use.
• Experience designing, building and deploying custom MCP servers from scratch, includingauthentication, tool design and error handling.
• Proficiency working with APIs, including custom code to manage rate limits, retries, paginationand authentication.
• Proficiency setting up and maintaining a data warehouse, with hands-on experience inSnowflake, Databricks or Google BigQuery.
• Experience building model-agnostic systems: portable prompts, abstraction layers and evals thatrun across providers.
• Experience building evals for AI systems: prompt evals, benchmarking against human baselinesand regression testing.
• First-hand understanding of GTM functions. You've worked in or directly alongside marketing,sales or customer success. You understand funnels, ICP, buying signals, pipeline coverage anddeal stages, and you decide what to automate by revenue impact.
• Fluency with the GTM stack and how data moves through it: CRM, marketing automation,enrichment, sales engagement and conversation intelligence. HubSpot is a plus.
• Excellent written and spoken English. You can explain a technical tradeoff to an executive in twominutes, write documentation a non-engineer can follow and coach non-technical teammatesthrough AI adoption.
• The ability to work US Eastern Time business hours.
• Comfort with ambiguity. You scope the problem, make the call and ship.Nice to have
• Experience with orchestration platforms such as n8n, Make or Zapier.
• Experience with enrichment and intent data tools such as Clay, ZoomInfo or Clearbit, and withbuilding lead-scoring models.
• Data scraping experience with tools such as BeautifulSoup, Scrapy or Puppeteer.
• Experience fine-tuning or heavily customizing models for production use.
• LLM observability tooling.
• Familiarity with brand-safety and compliance constraints on automated outputs.
• Time in RevOps or marketing operations, or at a B2B SaaS company.
• Familiarity with multi-unit retail.
• A track record of working remotely with US-based teams.