Deployed Engineer

Avoca AI; California; Hybrid; USD 95,000 - 135,000; Full time

Job summary

Avoca AI seeks a highly technical Deployment Engineer to join our remote team. You’ll embed with customers, understand operations, design tailored AI solutions, and deploy systems that deliver immediate impact from day one.

You will own deployments, integrations, and operational support of our voice agent products in live environments, diagnosing issues and optimizing performance while communicating complex technical concepts to diverse stakeholders.

Qualifications

• 2+ years of software engineering experience, preferably backend or systems-focused.
• Proficiency in Python (TypeScript/JavaScript a plus).
• Hands-on experience with microservices architectures, APIs, SQL/NoSQL databases, networking, and distributed systems.
• Familiarity with major cloud providers (AWS, GCP, or Azure).
• Experience diagnosing and debugging production systems and integration environments.

Responsibilities

• Embed with customers to understand their operations and deliver working AI solutions from day one.
• Deploy, integrate, and maintain the company's voice agent products within complex customer infrastructure.
• Build and maintain the infrastructure behind conversational AI APIs, integrations, monitoring, and feedback loops.
• Diagnose production issues and perform deep root-cause analysis across distributed systems, APIs, and LLM-powered workflows.
• Translate business requirements into technical architectures and deployment plans.
• Identify patterns across deployments and feed insights back into the product roadmap.
• Monitor and optimise product performance in production, working directly with LLMs and distributed systems.
• Communicate complex technical issues clearly to both technical and non-technical stakeholders.
• Document solutions, best practices, and troubleshooting processes to raise the whole team's operational bar.

Skills

Python

TypeScript/JavaScript

Microservices

APIs

SQL/NoSQL

Distributed systems

Cloud platforms

LLMs / prompt engineering

Vector databases

Production debugging

Tools

AWS

GCP

Azure

Job description

We're looking for a highly technical Deployment Engineer to join our remote team. As a DE, you'll embed directly with customers, understanding their operations, designing tailored AI solutions, and deploying systems that deliver immediate impact from day one. You'll take ownership of deployments, integrations, and operational support of the company's voice agent products in live customer environments, operating with high autonomy in ambiguous, high-stakes situations. This role requires deep technical expertise, strong root-cause diagnosis skills, and exceptional communication to keep our solutions running reliably in production.

Responsibilities:

• Embed with customers to understand their operations and deliver working AI solutions from day one.
• Deploy, integrate, and maintain the company's voice agent products within complex customer infrastructure.
• Build and maintain the infrastructure behind conversational AI APIs, integrations, monitoring, and feedback loops.
• Diagnose production issues and perform deep root-cause analysis across distributed systems, APIs, and LLM-powered workflows.
• Translate business requirements into technical architectures and deployment plans.
• Identify patterns across deployments and feed insights back into the product roadmap.
• Monitor and optimise product performance in production, working directly with LLMs and distributed systems.
• Communicate complex technical issues clearly to both technical and non-technical stakeholders.
• Document solutions, best practices, and troubleshooting processes to raise the whole team's operational bar.

Requirements:

• 2+ years of software engineering experience, preferably backend or systems-focused.
• Proficiency in Python (TypeScript/JavaScript a plus).
• Hands-on experience with microservices architectures, APIs, SQL/NoSQL databases, networking, and distributed systems.
• Familiarity with major cloud providers (AWS, GCP, or Azure).
• Experience diagnosing and debugging production systems and integration environments.
• Strong communicator, able to work with both technical and non-technical, customer-facing stakeholders.
• Experience with LLMs, prompt engineering, vector databases, or AI agent frameworks.
• Customer-facing technical experience is a plus.
• Ability to work remotely while collaborating with a high-performing team across US time zones.