Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
GitHub @ 3
Kubernetes @ 3
LLM @ 2
Prompt Engineering @ 2
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Customer.io is seeking a GTM AI Engineer to take AI agents from prototypes to production-grade systems that GTM teams can depend on. The team currently operates 11 production agents serving 120 active users and approximately 25,000 tool calls per day. This role owns the scale, reliability, and infrastructure layer for the agent fleet.
Responsibilities
- Take newly built agents from working v1 to production-ready systems by writing evaluations, hardening prompts and tool definitions, and refactoring prototype scaffolding into clean, production-quality code.
- Instrument tracing, logging, and monitoring across the agent fleet to identify regressions before they affect users.
- Build and maintain deployment pipelines for releasing agents, including environment parity and release hygiene on the Google Cloud Platform stack.
- Administer and manage how agents safely read from and write to databases at scale.
- Monitor agent behavior in production, triage issues, and deliver ongoing improvements.
- Partner with the GTM AI team so agent builders can focus on zero-to-one development while this role owns scale and reliability.
- Evaluate existing technical decisions and propose plans for improvement.
Requirements
- 4+ years of experience in software engineering, platform or infrastructure engineering, or a similarly technical role, ideally at a B2B SaaS company.
- Comfort working in the terminal daily and using a GitHub pull-request and deployment workflow.
- Cloud hosting experience with Kubernetes, virtual machines, or equivalent technologies; Google Cloud experience is strongly preferred.
- Experience with how agents interact with and edit databases, including hands-on database administration.
- Familiarity with LLM-based application development, including prompt engineering, tool or function calling, evaluations, and modern agent frameworks.
- Ability to prompt AI tools effectively, critically review their output, and direct them to test and quality-assure their own work.
- Ability to iterate quickly while maintaining consistency and reliability as systems scale.
- A clear technical point of view and willingness to question existing implementation decisions.
Compensation And Benefits
- Starting salary of $140,000–$170,000 USD, or equivalent in local currency, depending on experience and subject to market rate adjustment.
- 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for the employee and their family.
- 16 weeks of paid parental leave.
- Unlimited paid time off.
- Remote work and wellness stipends.
- Professional development budget.
Hiring Process
- 30-minute Zoom call with a recruiter.
- 45-minute Zoom call with the hiring manager.
- 45-minute Zoom call with a member of the GTM AI team.
- 60-minute live technical session with the team.
Final candidates will complete a background check and employment verifications.
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