Overview
You're building the technical backbone for ShipBob's go-to-market teams. This involves Salesforce architecture, data integrations between 5-10+ systems, building custom workflows and automations, and implementing AI-powered tools for the sales org. You report to the VP of Rev Ops and work closely with sales leadership, marketing ops, and IT. ShipBob sells 3PL fulfillment services to e-commerce brands, typically $50K-500K+ annual contracts.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | GTM/Sales Engineer (Rev Ops Function) |
| Sales Motion | N/A - Infrastructure role |
| Deal Complexity | N/A - Supporting consultative/enterprise sales |
| Sales Cycle | N/A - Enabling 2-6 month cycles |
| Deal Size | N/A - Supporting $50K-500K+ ACVs |
| Quota (est.) | N/A - Measured on system uptime, automation velocity, sales efficiency gains |
Company Context
Stage: Growth stage (1,582 employees, established player)
Size: ~1,600 employees across fulfillment centers and corporate
Growth: Scaling fulfillment network to 60+ centers globally. Heavy operational complexity with logistics + software.
Market Position: Established competitor in 3PL fulfillment space (competing with ShipMonk, Flexport, Deliverr/Shopify Fulfillment). Not the cheapest option but differentiate on tech platform + distributed network.
GTM Reality
Pipeline Sources:
- 40-50% Inbound - brands searching for "Shopify fulfillment" or outgrowing self-fulfillment, some PLG from website calculator tools
- 40-50% Outbound - AEs and SDRs targeting growing DTC brands (100-1000 orders/day), often cold outreach to ecommerce operators
- 10-20% Referrals/Partners - ecosystem partners like Shopify, BigCommerce, freight forwarders
SDR/AE Structure: Dedicated SDR team feeding pipeline to AEs. AEs run discovery/demos/negotiations. Handoff to onboarding/CS post-sale.
SE Support: Sales Engineers do technical demos for complex accounts (multi-warehouse, international fulfillment, custom integrations).
Competitive Landscape
Main Competitors: ShipMonk, Flexport, Shopify Fulfillment Network, Amazon MCF, regional 3PLs
How They Differentiate: Technology platform (WMS, integrations with 50+ platforms, distributed inventory capabilities) + network density for 2-day shipping reach
Common Objections: "Too expensive compared to our current 3PL," "We're not ready to give up control of fulfillment," "What if we outgrow you and need to switch again?"
Win Themes: Speed to market (vs building in-house), geographic coverage for fast shipping, platform integrations that reduce manual work
What You'll Actually Do
Time Breakdown
Building/Coding (40%) | System Config (30%) | Troubleshooting (20%) | Meetings (10%)
Key Activities
- Salesforce Development: Build custom objects, flows, validation rules, and Apex code to support complex deal structures (multiple warehouses per customer, usage-based pricing, renewal forecasting). You're in Salesforce admin/developer tools daily.
- Data Pipeline Engineering: Write Python or SQL scripts to sync data between Salesforce, the WMS (warehouse management system), billing systems, customer data platforms, and BI tools. A lot of ETL work to give sales teams accurate inventory/usage data.
- AI Implementation: Test and deploy AI tools the VP wants to pilot—think conversational intelligence (Gong/Chorus), AI email assistants, forecasting models, lead scoring. You're evaluating vendors, building integrations, and measuring ROI.
- Automation Building: Create Zapier/Make workflows, Salesforce flows, or custom scripts to eliminate manual data entry. Examples: auto-creating onboarding tasks when deals close, flagging at-risk renewals based on usage patterns, enriching leads with warehouse capacity data.
- Troubleshooting: Field tickets from AEs and SDRs when systems break or data looks wrong. "Why isn't this opportunity showing the right pricing?" "The integration stopped syncing orders." You debug and fix.
The Honest Reality
What's Hard
- Complex Data Model: ShipBob's business is operationally complex—multiple SKUs per customer, inventory across warehouses, usage-based billing that changes monthly. The data model in Salesforce reflects this mess. You'll spend a lot of time just understanding how data flows.
- Competing Priorities: Sales leadership wants new AI tools yesterday. The VP wants clean data architecture. IT wants security reviews. Marketing wants attribution reporting. You're constantly triaging what gets built next and explaining to stakeholders why their request isn't done yet.
- "AI-Native" Ambiguity: They're pitching this as building "next generation AI infrastructure," but in reality you're probably starting with basic integrations and automations. The AI vision is aspirational—you'll spend months on unglamorous plumbing work (data cleaning, API rate limits, system migrations) before the cool AI stuff ships.
- Logistics + Tech Hybrid: ShipBob isn't a pure SaaS company. You're supporting sales of physical fulfillment services, which means the CRM has to talk to warehouse systems, freight systems, billing systems based on actual shipments. More moving parts than typical B2B SaaS.
What Success Looks Like
- System Uptime: Core integrations run reliably. Sales reps aren't blocked by system errors or missing data.
- Velocity Metrics: Time from lead to opportunity to closed-won decreases because you've automated manual steps. AEs spend less time on admin, more time selling.
- Adoption: The AI tools or automations you build actually get used by reps (not ignored). You measure login rates, workflow completion, tool engagement.
- Rev Ops Influence: Your work enables better forecasting, pipeline visibility, and territory planning. The Rev Ops team gets a seat at the strategy table because the data is trustworthy.
Who You're Supporting
Primary Internal Customers:
- AEs (Account Executives): Need accurate customer data, pricing tools, streamlined deal workflows. They're in Salesforce 5-10 times per day.
- SDRs: Need good data enrichment, task automation, lead scoring. They're making 50-80 touches per day and want tools to help prioritize.
- Rev Ops/Sales Leadership: Need dashboards, forecasting models, pipeline analysis. They're asking you to pull custom reports constantly.
What They Care About:
- AEs: "Does this save me time or make me slower?" They'll resist new tools if it adds clicks. They want auto-populated fields, fewer manual updates.
- SDRs: "Does this help me book more meetings?" They want lead scoring that actually predicts interest, not garbage-in-garbage-out models.
- Leadership: "Can I trust this forecast number?" They need data integrity and want to understand how the systems calculate pipeline coverage, conversion rates, etc.
Requirements
- Salesforce Chops: You've built things in Salesforce beyond basic admin. Comfortable with flows, validation rules, ideally some Apex or API work. Salesforce Admin certification helpful.
- Coding Ability: You can write Python or JavaScript for integrations and automation. Not a full software engineer role, but you're scripting regularly—API calls, data transformations, webhook handlers.
- Data/SQL Skills: You write SQL queries to analyze pipeline data, troubleshoot sync issues, or pull reports. Comfortable with concepts like joins, aggregations, data modeling.
- Systems Thinking: You understand how CRM, marketing automation, CPQ, billing, and data warehouses fit together. You've worked in a multi-system GTM stack before.
- Logistics/SaaS Context (Nice to Have): ShipBob's business model is unusual—selling logistics services with software on top. Understanding usage-based pricing, inventory management, or supply chain helps you grasp what the sales team is actually selling.
- Scrappiness: This is "early in the journey" per the post. You're building from scratch in some areas, inheriting technical debt in others. You need to be comfortable with ambiguity and figuring things out as you go.