Go-To-Market Engineer - Automox

Automox is seeking an innovative, results-driven Go-to-Market Engineer to execute hands-on, multi-channel marketing strategies that drive predictable engagement and pipeline growth. As our Go-to-Market Engineer, you'll build and run the AI tools, integrations, and data pipelines that Automox's go-to-market teams (Sales, Professional Services, Alliances, and Marketing) use every day. You'll take requests straight from team leads, scope them, and ship working tools on AWS with Claude and other LLMs.

This is a hands-on builder role on the Growth team in Marketing. You'll own work end to end, from the first conversation with a sales leader to the production deploy and the training session that gets people using it.

What You’ll Own & Drive

• Build internal apps and AI agents that sales and services teams use with customers.
• Build and host MCP servers that connect AI agents to Automox systems, CRM data, and marketing tools.
• Run LLM pipelines in production for transcription, search, classification, and content generation.
• Build and maintain data pipelines and dashboards from Salesforce, HubSpot, Gong, Outreach, and GA4.
• Write Claude skills and automations for go-to-market teams, and train people to use them.
• Test AI products before launch, and advise leadership on AI tools and proposals.

What You Bring to the Table

• Production software in TypeScript and Python, with tests and CI/CD.
• LLM applications in production on the Anthropic and OpenAI APIs: prompt design, model choice, tool use, and token cost.
• MCP servers and agent tools, with SSO or OAuth sign-in and least-privilege access.
• Agent workflows with evaluation and human review: test sets, LLM-as-judge scoring, and approval steps.
• API integrations with go-to-market systems such as Salesforce, HubSpot, Gong, and Outreach.
• SQL and data modeling in PostgreSQL, including embeddings and vector search.
• AWS: ECS or EC2, RDS, S3, CloudFront, IAM, and GitHub Actions deploys without stored keys.
• A track record of turning loose requests from sales and marketing leads into scoped builds, then shipping and iterating.
• Clear writing and documentation, and the ability to explain AI tools to people who aren't engineers.
• Solid security habits: secrets management, access control, and AI governance review before connecting a new tool.

Nice to Have

• Experience with Claude Code, Codex, Antigravity, Opencode, or similar coding agents, including skills, subagents, and project rules.
• Next.js and React for internal tools, including generated PDFs.
• BigQuery, GA4, and Google Ads data.
• Okta SSO for internal apps and hosted MCP servers.
• Infrastructure as code with CloudFormation or Terraform.
• AI search visibility: llms.txt, schema markup, and citability.
• A background in IT operations, endpoint management, or security, such as patching and vulnerability response.