Enterprise AI Deployment Engineer

Quantix Search; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Quantix Search is partnering with a top US AI company building enterprise AI agents for customer interactions across voice, chat, email, and messaging. The role sits between engineering, product, and customers, owning hands-on implementation to launch and scale enterprise-grade AI systems.

You will own deployments, configure behaviours and guardrails, and build integrations across environments while collaborating with technical stakeholders to turn feedback into product improvements.

Qualifications

• Experience in a technical customer-facing role.
• Strong coding fundamentals and ability to build integrations end to end.
• Experience shipping production systems and iterating based on customer outcomes.
• Strong communication and ability to influence technical stakeholders.
• Comfortable operating in ambiguity and moving quickly.
• Exposure to LLMs, AI agents, prompt design, evaluation, or agent workflows is a strong plus.

Responsibilities

• Own enterprise AI agent deployments from scoping through launch and iteration.
• Configure agent behaviour, workflows, guardrails, and quality controls.
• Build and validate integrations across customer environments and internal systems.
• Work directly with technical stakeholders to define requirements and drive delivery.
• Translate customer feedback into product improvements alongside engineering.

Skills

Coding fundamentals

End-to-end integrations

Production systems

Strong communication

Stakeholder influence

Ambiguity management

LLMs / AI agents exposure

Job description

Quantix Search is partnering with a top US AI company building enterprise AI agents for customer interactions across voice, chat, email, and messaging. The role sits between engineering, product, and customers, owning hands-on implementation to launch and scale enterprise-grade AI systems.

You will own deployments, configure behaviours and guardrails, and build integrations across environments while collaborating with technical stakeholders to turn feedback into product improvements.