About Avoca

Avoca is transforming how home service companies engage with their customers. Our AI-powered conversational agents handle every high-value inbound call, including booking jobs, qualifying leads, and driving higher revenue—all at a speed and consistency unmatched by human call centers.

We’ve expanded to 100 employees in under two years, backed by a high-energy, in-office culture across our NYC headquarters and Santa Barbara office. In a $500B+ market where missed calls mean lost business, we’re building the category-defining platform for AI-driven customer engagement.

We’re serving the largest brands in home services, and grew 10x in 2025. With a high-performance, in-office team in NYC, we’re moving fast to capture a massive, underserved market where 85% of missed calls go to competitors. Every hire here has an immediate and visible impact.

Role Overview

We are seeking a highly skilled and motivated Deployment Engineer (DE) to join our remote team.

DEs are highly technical self-starters who take ownership of deployments, integrations, and operational support of Avoca’s voice agent products in customer environments.

This role requires deep technical expertise, strong root-cause diagnosis skills, and exceptional communication to ensure our solutions operate reliably in complex production environments.

Key Responsibilities

• Deploy, integrate, and maintain Avoca voice agent products in complex customer infrastructures.

• Diagnose production issues and perform deep root-cause analysis across distributed systems, APIs, and LLM-powered workflows.

• Analyze and resolve complex technical scenarios involving Large Language Models (LLMs), system architecture, and scalability challenges.

• Collaborate with cross-functional teams and customers to understand requirements and deliver tailored technical solutions.

• Monitor and optimize product performance in production environments leveraging LLMs and distributed systems.

• Communicate complex technical issues clearly to both technical and non-technical stakeholders.

• Document solutions, best practices, and troubleshooting processes to improve team knowledge and operational efficiency.

• Take initiative to improve deployment tooling, reliability, and system observability.
  

Core Competencies

Troubleshooting & Root Cause Analysis

• Systematically diagnose and resolve complex technical problems.

• Perform structured debugging across infrastructure, APIs, networking, and application layers.

Communication

• Clearly explain technical concepts and tradeoffs to diverse audiences including customers.

Fundamental Knowledge

• Strong foundation in computer science, system architecture, networking, databases, and distributed systems.

• Ability to reason from first principles.

Domain Knowledge

• Understanding of Large Language Models (LLMs), their limitations, and operational considerations.

Decision Making

• Make fast, effective decisions that balance technical solutions with business impact.

Ownership & Self-Starter Mentality

• Proactively take ownership of problems, deployments, and improvements.
  

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.

• Hands-on experience with:

  • Microservices architectures

  • APIs

  • SQL / NoSQL databases

  • Networking and distributed systems

• Experience diagnosing and debugging production systems and integration environments.

• Familiarity with AI/ML systems, Prompt Engineering, particularly LLM-powered applications, is highly desirable.

• Strong analytical and problem-solving skills.

• Excellent verbal and written communication.

• Experience in customer-facing technical roles is a plus.

Why Join Avoca

• Work remotely while collaborating with a high-performing team across US time zones.

• Join a fast-moving startup environment where engineers have real ownership and impact.

• Contribute to cutting-edge voice agent technology transforming service industries.

• Solve challenging real-world AI deployment problems at scale.

• Continuous learning and growth in a high-velocity, innovation-driven culture.