SpaceX Software Engineer on the Starlink Enterprise team at SpaceX focused on improving data quality and building AI integrations for go-to-market systems. Develops AI agents and automations to enhance sales and operational workflows.
Responsibilities
Improve data hygiene and quality across go-to-market systems — identify bad, missing, duplicate, and stale records; implement validation, enrichment, and remediation so higher-quality data enters our system of record, opportunity, partner/reseller, and enablement workflows
Raise the quality of inputs to AI agents and analytics so outputs (recommendations, deal status, enablement answers, reporting) are more accurate, trustworthy, and actionable
Build integrations across internal tools and external systems so deal, customer, and partner context flows cleanly between sales, channel ops, and operational platforms — reducing manual re-entry and preventing quality issues at the source
Develop Model Context Protocol (MCP) servers and related interfaces that connect AI assistants (including Grok) to internal and external go-to-market systems, with an emphasis on reliable, well-scoped access to the right data and tools
Design, ship, and iterate AI agents that power Starlink Enterprise go-to-market workflows
Contribute to AI-powered applications and automations that accelerate lead-to-revenue cycles, working within the additional datasets and systems architecture owned by the team
Instrument data quality and agent performance with monitoring and feedback loops — catching regressions early and tying improvements to outcomes (e.g., cleaner pipeline, faster cycle times, higher adoption and trust)
Partner closely with sales, sales ops, channel/reseller ops, and enablement to turn recurring data-quality problems and manual processes into durable automations and standards
Create reusable tools, checks, and documentation that help the team maintain data quality and extend agents over time
Qualification
Bachelor’s degree in computer scienceExperience building AI agentsExperience designing APIsExperience with agent evaluation
Required
Bachelor’s degree in computer science, data science, physics, mathematics, or another STEM discipline
1+ years of professional data engineering or software engineering experience (internship experience applicable)
1+ years of development experience in Python or another modern programming language (SQL, etc.)
Preferred
Experience improving CRM data quality (deduping, enrichment, validation rules, field completeness, source-of-truth discipline)
Experience building AI agents, LLM-powered applications, or tool-using assistants that integrate with real business systems (APIs, CRMs, ticketing, data warehouses)
Experience designing APIs, webhooks, or integration layers that connect heterogeneous systems and keep data consistent across them
Familiarity with Model Context Protocol (MCP) or similar patterns for exposing tools and data sources to AI systems
Experience with CRM and go-to-market tooling; familiarity with Clay, HubSpot, Apollo, or similar sales engagement / enrichment platforms is a plus
Professional experience supporting sales, sales ops, channel/reseller, or revenue operations workflows with data and automation
Experience with SQL and modern data tooling; exposure to Grok, internal AI platforms, or comparable LLM developer tooling is a plus
Experience with agent evaluation, guardrails, permissions, and human-in-the-loop patterns for production AI systems
