GCP Devops

Machine Learning Technologies, LLC; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Machine Learning Technologies, LLC in Austin, TX is seeking a DevOps/Platform Engineer to automate provisioning, deployment, and operation of customer environments on GCP and AWS. You will ensure repeatable, secure, and observable environment creation.

You will build CI/CD pipelines for pre-built artifacts and customer configurations, manage lifecycle, monitor, and control costs while collaborating with architects and data engineers on RAG workflows.

Qualifications

• 5+ years in DevOps, SRE, or platform engineering with production IaC.
• Hands-on Terraform on both Google Cloud and AWS.
• CI/CD experience.
• Practical security operations: secrets managers, IAM, private networking, audit logging.
• Google Cloud DevOps Engineer and/or AWS DevOps / SysOps certification.
• Experience deploying contact-center or conversational platforms.

Responsibilities

• Implement and maintain Infrastructure-as-Code for GCP projects and AWS accounts.
• Automate service enablement, networking, IAM bindings, secrets, and baseline logging on both clouds.
• Provision and operate infrastructure for RAG / knowledge pipelines: document stores, vector or search indexes, embedding/index jobs, schedulers, and secrets.
• Build CI/CD pipelines that deploy pre-built application artifacts, customer-specific configuration, and knowledge-index refresh jobs.
• Manage environment lifecycle: create, update, snapshot/backup where relevant, and tear down.
• Implement monitoring, alerting, and dashboards sufficient for go-live and handoff, including pipeline job failures.
• Partner with the Architect to turn designs into reusable modules; partner with specialists and the Data Engineer to wire application and RAG deploy steps.
• Control cost via budgets, labels/tags, and idle-environment policy.

Job description

Job Description

Automate provisioning, deployment, and operational readiness of customer environments on GCP and AWS, including the infrastructure that runs RAG / knowledge pipelines. You make environment creation and application promotion repeatable, secure, and observable. You do not develop the conversational applications or the retrieval logic.

What success looks like:

• A new customer environment can be stood up from approved modules with minimal manual console work.
• CI/CD pipelines promote the pre-built CCAI, voice, and chat packages plus customer config in a controlled way.
• Logging, monitoring, secrets, and teardown/lifecycle processes exist for every environment, including knowledge / RAG jobs and stores.

Key responsibilities:

• Implement and maintain Infrastructure-as-Code for GCP projects and AWS accounts.
• Automate service enablement, networking, IAM bindings, secrets, and baseline logging on both clouds.
• Provision and operate infrastructure for RAG / knowledge pipelines: document stores, vector or search indexes, embedding/index jobs, schedulers, and secrets.
• Build CI/CD pipelines that deploy pre-built application artifacts, customer-specific configuration, and knowledge-index refresh jobs.
• Manage environment lifecycle: create, update, snapshot/backup where relevant, and tear down.
• Implement monitoring, alerting, and dashboards sufficient for go-live and handoff, including pipeline job failures.
• Partner with the Architect to turn designs into reusable modules; partner with specialists and the Data Engineer to wire application and RAG deploy steps.
• Control cost via budgets, labels/tags, and idle-environment policy.

Required qualifications:

• 5+ years in DevOps, SRE, or platform engineering with production IaC.
• Hands-on Terraform on both Google Cloud and AWS.
• CI/CD experience
• Practical security operations: secrets managers, IAM, private networking, audit logging.
• Google Cloud DevOps Engineer and/or AWS DevOps / SysOps certification.
• Experience deploying contact-center or conversational platforms.
• DevOps, Terraform, AWS CDK, GCP, CI/CD, Cloud Build, CodePipeline, IAM, secrets, landing zone, platform engineering, vector database, Vertex AI, Bedrock

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.