AI Applications Engineer

Five9; United States; On-site; USD 130,000 - 190,000; Full time

Job summary

Five9 is seeking an AI Platform Engineer to build and operate the AI platform that powers its cloud contact center solutions. You will manage cloud environments, deployment pipelines, model runtime, and security guardrails to enable rapid, safe AI delivery.

The role emphasizes scalable infrastructure, reproducible environments, and close collaboration with cross-functional teams to ship AI capabilities with reliability and observability.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years in platform, DevOps, infrastructure, or MLOps engineering, including hands-on operation of production cloud systems.
• Deep hands-on cloud experience (Google Cloud preferred) with infrastructure-as-code (Terraform) and containers/orchestration (Docker, Kubernetes).
• Strong CI/CD engineering — building delivery pipelines with automated testing and security gates.
• Experience running ML/LLM or data-intensive systems in production (MLOps/LLMOps: serving, evaluation, versioning, agent runtime).
• Solid security-engineering fundamentals (IAM, secrets, network egress, policy-as-code) and building to enterprise governance.
• Observability and reliability practice (monitoring, logging, SLOs, incident response) with a builder-enablement mindset.

Responsibilities

• Platform build & operation — Build and operate the AI platform on the cloud, ensuring production-grade security and reliability.
• Infrastructure as code — Provision and manage infrastructure as code (e.g., Terraform) for reproducible environments.
• CI/CD & delivery pipelines — Build and maintain pipelines that enable rapid, secure deployment.
• Model & agent runtime (MLOps/LLMOps) — Stand up serving, evaluation, versioning, and runtime tooling.
• Data & integration plumbing — Create secure connectors and data pipelines for AI solutions.
• Security & governance guardrails — Implement IAM, secrets management, and policy-as-code with InfoSec.
• Reusable components & paved road — Develop shared libraries and self-service tools for teams.
• Observability & reliability — Instrument monitoring, logging, costs, and SLOs; manage incidents.

Skills

Google Cloud

Terraform

Docker

Kubernetes

CI/CD

MLOps/LLMOps

Security & IAM

Observability

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Terraform

Docker

Kubernetes

Job description

Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide.

Living our values everyday results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves.

AI Applications Engineer

ABOUT THE ROLE

Five9 is a leading provider of cloud contact center software, bringing the power of Five9 AI and automation to organizations worldwide. The Enterprise-AI Team drives Five9's internal adoption of AI — turning emerging capability into real business outcomes across the company.

The AI Platform Engineer builds and operates the platform Five9's AI solutions run on. Where the AI Automation Engineer builds solutions and automations, you build the paved road they build on — the cloud environment, delivery pipelines, model and agent runtime, data and integration plumbing, security and governance guardrails, and the reusable components that let the team and the business ship AI quickly, safely, and reliably. You keep the platform secure, observable, and production-grade so every AI solution has a dependable foundation, and you stay current on the fast-moving AI infrastructure and tooling landscape.

HOW YOU CONTRIBUTE

• Platform build & operation — Build and operate the AI platform on the cloud — compute, environments, networking, and runtime — and keep it production-grade, secure, and reliable.


• Infrastructure as code — Provision and manage infrastructure as code (e.g., Terraform) so environments are reproducible, reviewable, and auditable.


• CI/CD & delivery pipelines — Build and maintain the pipelines — build, test, security gates, deploy — that solution builders and business teams ship through.


• Model & agent runtime (MLOps / LLMOps) — Stand up model and agent serving, evaluation, prompt and version management, and the tooling to run LLM- and agent-based systems in production.


• Data & integration plumbing — Build the secure connectors, data pipelines, and integration surface that AI solutions draw on.


• Security & governance guardrails — Engineer security, data‑classification, and responsible‑AI controls into the platform (IAM, secrets, egress, policy‑as‑code) with InfoSec.


• Reusable components & paved road — Build shared libraries, templates, and self‑service tooling so builders and business teams move fast within guardrails.


• Observability & reliability — Instrument monitoring, logging, cost, and SLOs; own platform reliability and incident response.


• Enable the builders — Partner with the Automation Engineer, the architect, and business builders so the platform meets real build needs; document and support it.

SKILLS, COMPETENCIES & QUALIFICATIONS — REQUIRED

• Bachelor's degree (or equivalent experience) in Computer Science, Engineering, or a related field.


• 3+ years in platform, DevOps, infrastructure, or MLOps engineering, including hands‑on operation of production cloud systems.


• Deep hands‑on cloud experience (Google Cloud preferred) with infrastructure‑as‑code (Terraform) and containers / orchestration (Docker, Kubernetes).


• Strong CI / CD engineering — building delivery pipelines with automated testing and security gates.


• Experience running ML / LLM or data‑intensive systems in production (MLOps / LLMOps: serving, evaluation, versioning, agent runtime).


• Solid security‑engineering fundamentals (IAM, secrets, network egress, policy‑as‑code) and building to enterprise governance.


• Observability and reliability practice (monitoring, logging, SLOs, incident response) with a builder‑enablement mindset.

SKILLS, COMPETENCIES & QUALIFICATIONS — PREFERRED

• Experience building an internal developer platform or self‑service \"paved road\" for other engineers.


• Agent / LLM infrastructure (orchestration, retrieval, tool integration, model gateways).


• Contact center / CX technology exposure (Five9 or comparable).


• Cloud (Google Cloud) or Kubernetes certifications.


• Familiarity with responsible‑AI and model‑risk controls at the platform level.

WHERE THIS ROLE SITS

• Primary focus: build & operate the AI platform — The foundation every AI solution runs on — cloud, pipelines, runtime, guardrails, and reusable components.


• Distinct from the AI Automation Engineer — The Automation Engineer builds solutions and automations ON the platform; this role builds and runs THE platform they build on.


• Partners with the architect & platform / DevOps — Implements the platform to the technical standards, with Enterprise Architecture, InfoSec, and platform / DevOps.

KEY RELATIONSHIPS

No direct reports (provides technical leadership on the platform). Key partners: the AI Automation Engineer, the solutions architect, platform / DevOps, information security, business builders. You build and operate the platform the whole team — and the business's own builders — depend on.

Five9 embraces diversity and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we are. Five9 is an equal opportunity employer.

View our privacy policy, including our privacy notice to California residents here: https://www.five9.com/pt-pt/legal.

Note: Five9 will never request that an applicant send money as a prerequisite for commencing employment with Five9.