CRM Engineer / Salesforce & Revenue Systems Engineer
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- Build a trustworthy CRM platform model and customize it with secure engineering discipline
- Connect CRM to the enterprise and operate changes safely across data, APIs and releases
- Turn CRM into an AI-native customer operating system with measurable reliability and human control
Benchmark: Anthropic Salesforce Developer + Salesforce Developer, Partnerships + Staff Software Engineer, GTM Systems; OpenAI CRM / Salesforce systems and Growth Martech signals (current Sep 2026). Market refresh: CRM workflows; Salesforce platform engineering; customer data models; APIs and event-driven integration; OAuth/identity; DevOps/QA; data quality; agentic CRM; AI evaluation; privacy, controls and production reliability.
Who’s Hiring Right Now
US openings posted in the last 7 days at Anthropic — this role’s own benchmark employers — refreshed daily, as of 2026-11-01. Pulled directly from each company’s public job board; not exhaustive, and postings close fast — worth confirming the details on the employer’s own site before applying.
Build a trustworthy CRM platform model and customize it with secure engineering discipline
CRM platform architecture, customer lifecycle + data model
Coverage: CRM Architecture / Sales & Service Workflows / Customer Data / Data Modeling / Salesforce Platform
Extensibility, automation + identity/security
Coverage: Apex / Declarative Automation / OAuth-OIDC / Access Control / Secure CRM Engineering
Connect CRM to the enterprise and operate changes safely across data, APIs and releases
APIs, event-driven integration + iPaaS patterns
Coverage: REST APIs / Platform Events / Integration Architecture / MuleSoft / Event-Driven Systems
Testing, DevOps + governed release engineering
Coverage: CRM DevOps / Git / CI-CD / QA / Sandboxes / Release Governance / Observability
Turn CRM into an AI-native customer operating system with measurable reliability and human control
Agentic CRM, tool use + human-in-the-loop workflows
Coverage: Agentforce / AI Agents / MCP / Workflow Automation / Human Review / Customer Operations
Evaluation, production reliability + business controls
Coverage: AI Evals / Regression Testing / Monitoring / Privacy / Safety / SLOs / CRM Governance
Role-Readiness Proof / Capstone
Engineer a production-grade CRM operating system for a simulated B2B company. Model accounts, contacts, leads, opportunities, products and service cases; implement lifecycle automation plus Apex/custom logic where justified; integrate at least two adjacent systems through REST/event-driven patterns; enforce OAuth/least privilege and sensitive-data controls; build CI/CD, automated tests and release gates; add a customer-data or semantic layer; implement one AI/agent workflow with explicit permissions and human approval; instrument adoption, failure, latency and business metrics; then run a release, incident and rollback exercise with an architecture decision record and runbook.
Proof Rubric
- Prove correct CRM data and process architecture
- maintainable customization
- API/event contract quality
- authentication and authorization
- data quality and reconciliation
- automated tests and safe releases
- observable integrations
- reliable AI/agent behavior with evals and human control
- privacy and auditability
- incident recovery
- measurable adoption or cycle-time impact
- and clear reasoning about configure-vs-code, platform-vs-custom, synchronous-vs-event-driven and automation-vs-human tradeoffs