What are the responsibilities and job description for the Azure Platform Architect / Engineer (Gen AI & AI/ML Integration) position at AceStack?
100% Onsite position from day 1. Apply only if skills-set matches to you.
Job Title: Azure Platform Architect / Engineer (Gen AI & AI/ML Integration)
Location: Atlanta, GA (Onsite from day 1)
Long Term Contract
Job Summary: We are seeking an experienced Azure Platform Architect / Engineer to design, implement, and manage scalable AI/ML cloud architectures. The ideal candidate will have expertise in Azure services, Gen AI integration, cross-cloud platform implementation, Infrastructure as Code (IaC), MLOps, security, and DevOps.
Key Responsibilities:
Azure Platform Architecture
- Design and implement scalable, secure, and cost-effective AI/ML architectures using Azure.
- Utilize Azure Kubernetes Service (AKS), Azure Functions, and Azure Logic Apps for serverless and container-based AI/ML applications.
- Implement data pipelines and big data processing using Azure Data Lake, Azure Data Factory, and Azure Synapse Analytics.
Gen AI & AI/ML Integration
- Lead the design and implementation of AI/ML pipelines integrating with Azure Machine Learning and Azure OpenAI Service.
- Develop and optimize ML models using Azure Cognitive Services (Vision, Speech, Text Analytics, Personalizer, and Translator).
- Implement MLOps practices for model versioning, automated testing, and continuous deployment.
- Utilize Azure OpenAI to create foundation models and build generative AI applications.
Cross-Cloud Platform Implementation
- Design and implement hybrid AI solutions across Azure, AWS, and Google Cloud.
- Develop integration strategies for seamless data flow and model deployment across multiple cloud environments.
- Implement multi-cloud governance and security best practices.
Infrastructure as Code (IaC)
- Develop and maintain Terraform or Bicep code for Azure infrastructure provisioning and third-party AI services integration.
- Implement modular and reusable configurations for AI/ML environments.
- Utilize Terraform/Bicep to manage GPU-enabled instances, distributed training clusters, and scalable AI workloads.
Azure Administration & Security
- Manage Azure resources for AI workloads, including Azure ML Compute, Azure Batch AI, and AKS clusters.
- Implement robust security measures for AI/ML workloads using Azure Key Vault, RBAC, and network security best practices.
- Set up monitoring and alerting using Azure Monitor, Application Insights, and Log Analytics.
CI/CD & DevOps
- Configure and customize CI/CD pipelines for AI/ML model deployment and Terraform/Bicep infrastructure automation.
- Integrate Azure DevOps and GitHub Actions for AI model and infrastructure deployment.
- Implement GitOps practices for managing AI infrastructure deployments.
Collaboration & Documentation
- Utilize GitHub/GitLab for version control, code reviews, and AI/ML model development.
- Document AI/ML pipelines, architectures, and infrastructure in Confluence for team collaboration.
Must-Have Qualifications:
Overall IT experience: 12-16 Years
- 5 years of experience designing and implementing AI/ML platforms on Azure.
- Expertise in Azure AI services such as Azure OpenAI, Azure Machine Learning, and Cognitive Services.
- Strong experience in cross-cloud platform implementation (Azure, AWS, Google Cloud).
- Proficiency in Terraform, Bicep, Azure DevOps, and CI/CD for AI/ML workloads.
- Strong Python programming skills for ML model development.
- Knowledge of containerization (Docker, Kubernetes, AKS).
- Excellent problem-solving and communication skills.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field (or equivalent experience).
If anyone if interested, please share your resume to bishnuu@acestackllc.com
