Cloud Machine Learning Engineer

Brooksource; United States; On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

401(k) Matching Plan

6 Paid Holidays

Job summary

Brooksource is partnering with a Fortune 500 healthcare insurer to build and operate a centralized AI platform. We seek a mid-level Cloud Machine Learning Engineer for hands-on work at the intersection of Cloud Platform Engineering and ML Ops, focusing on cloud services, governance, and secure model deployments.

The role emphasizes IaC, automation, and production operations across AWS and Azure, with responsibilities spanning model-serving integrations and GenAI enablement in a regulated

Qualifications

• Strong Python proficiency with production-quality code practices.
• Hands-on cloud engineering experience in AWS and/or Azure, incl. IAM and networking.
• Experience with IaC, CI/CD, and secure cloud service design.

Responsibilities

• Build and operate enterprise cloud services enabling AI model access, governance, usage tracking, and observability.
• Write and maintain production-grade Python scripts, services, and APIs.
• Develop IaC (Terraform/CloudFormation) and automate deployments via CI/CD across AWS/Azure.
• Implement access controls, secrets management, logging, monitoring, and secure service connectivity for production AI services.
• Support model-serving integrations and operationalize GenAI solutions in alignment with security and Responsible AI guidelines.

Skills

Python

Cloud engineering

Security & IAM

Observability

GenAI/LLMOps

Tools

Terraform

CloudFormation

CI/CD

Git

Job description

Reports to/Team Dynamic: Reports to the Senior Manager of Machine Learning Engineering; works closely with the Lead and Senior Cloud MLEs on a collaborative, fast-growing AI platform team.

About the Role:

Our Brooksource Fortune 500 healthcare insurance client is building the centralized AI platform that the rest of their enterprise runs on — and they’re looking for a mid-level Cloud Machine Learning Engineer to help build and operate it. This is a hands-on engineering role at the intersection of Cloud Platform Engineering and Machine Learning Engineering, contributing independently to the shared cloud services, controls, and tooling behind the client’s centralized AI Gateway and Machine Agentic Governed Intelligence (MAGI) Framework.

You’ll help ensure enterprise AI endpoints, models, and services are deployed, governed, monitored, and consumed in line with strict security, compliance, and healthcare regulatory requirements. The primary focus is cloud platform engineering — infrastructure, networking, Infrastructure as Code, automation, access controls, observability, and production operations across AWS and Azure. The secondary focus is Machine Learning Engineering and LLMOps — supporting model-serving integrations, evaluating new AI capabilities, and helping operationalize governed GenAI and agentic AI solutions. Over time, you’ll grow into a subject matter expert in responsible AI platform operations and advise other engineering teams on building scalable, governed, and observable AI solutions.

What You’ll Do:

• Build and operate the enterprise cloud services that enable AI model access, endpoint governance, usage tracking, and operational monitoring through the AI Gateway and MAGI Framework.
• Write and maintain production-quality Python — scripts, services, automation, SDKs, and APIs — using reusable, testable, maintainable code.
• Build, modify, and troubleshoot Infrastructure as Code (Terraform and/or CloudFormation) and automate deployments through CI/CD pipelines across AWS and Azure environments.
• Implement and manage access controls, secrets, networking, and secure service-to-service connectivity, along with logging, monitoring, observability, and alerting for production AI services.
• Support model-serving integrations and help operationalize GenAI and agentic AI solutions in alignment with the client’s security, compliance, observability, and Responsible AI frameworks.
• Manage APIs, service endpoints, and endpoint lifecycle, and contribute to production troubleshooting, operational support, and platform governance.

What You Bring:

• Strong professional Python proficiency, plus hands-on cloud experience designing, deploying, and supporting solutions in AWS and/or Azure (networking, security, IAM, and cloud-native services).
• Infrastructure as Code experience — able to build, modify, and troubleshoot Terraform and/or CloudFormation — along with CI/CD, Git, and solid software engineering fundamentals.
• Cloud networking and connectivity knowledge: private networking, VPC/VNet design, DNS, routing, load balancing, and secure API connectivity.
• Cloud platform and operational experience: IAM/RBAC, secrets management, observability, alerting, endpoint/API lifecycle management, and production troubleshooting.
• Exposure to Machine Learning platforms or MLOps — model deployment, model serving, ML workflows, or production ML/GenAI services — with a foundational understanding of machine learning, GenAI, and cloud AI concepts.
• Preferred: Databricks (Model Serving, Unity Catalog, Delta Lake, Mosaic AI, Asset Bundles), AI/API Gateway technologies, LLMOps, RAG or agentic workflows, AI governance/security (PII/PHI, prompt-injection defense, auditability), FinOps, and AWS/Azure/GCP/Databricks certifications.

Why Join Us?

• 401(k) Matching Plan
• Relationship Driven Process to Find Your Best Fit
• 6 Paid Holidays
• Regular Meetings to Ensure Quality in Your Engagement

About Us:

At Brooksource, relationships are the foundation of everything we do. Since 2000, we’ve built lasting partnerships with clients, consultants, and internal teams to deliver an exceptional experience across every engagement. As a trusted IT and Engineering services provider, Brooksource supports Fortune 500 organizations through Experience-Driven Staffing, Professional Services, and Elevate, our proprietary Workforce Transformation program. Whether you’re hiring for software development, cloud computing, cybersecurity, data analytics, or enterprise IT, our customized staffing solutions are designed to align with your company’s unique goals, culture, and technology stack. We offer flexible hiring models, including contract, contract-to-hire, and direct placement to meet your evolving business needs.

We are a certified partner of leading platforms, including Salesforce, AWS, Microsoft, and Google Cloud, enabling us to deliver scalable, end-to-end technology solutions. With a growing national footprint, Brooksource is redefining expectations in IT consulting, engineering services, and technology workforce solutions.

EEO Statement:

Brooksource is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, physical or mental disability, protected medical condition as defined by applicable state or local law, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances.

Pay Disclaimer:

The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.