ML / AI Platform Architect
Avacend Inc
United States
15 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Audit Trail
Microsoft Azure
Cloud Computing
Cloud Engineering
Identity and Access Management
Python (Programming Language)
Azure Machine Learning
Feature Engineering
Large Language Models
Kubernetes
+4 more
Machine Learning Operations
Virtual Agents
Software Version Control
Docker
Job description
- Design and own the end-to-end architecture for enterprise AI/ML platforms.
- Build and operationalize Feature Store and Model Catalog capabilities to support reusable feature engineering, model versioning, and self-service ML adoption.
- Develop and manage Agentic AI platform infrastructure, including agent runtimes, orchestration frameworks, tool integrations, and agent lifecycle management.
- Establish and maintain Agent Catalog capabilities to enable deployment, discovery, monitoring, and governance of AI agents.
- Design and implement AI governance controls, including access management, policy enforcement, audit logging, monitoring, and observability.
- Develop MLOps pipelines and cloud-native deployment frameworks to support scalable AI/ML workloads.
- Collaborate with Data Science, Engineering, Security, and Business teams to deliver enterprise AI solutions.
Requirements
- 7+ years of experience in AI/ML platform engineering, cloud architecture, or MLOps.
- Strong experience with AI/ML platforms, Feature Stores, Model Registries/Catalogs, and MLOps frameworks.
- Hands-on experience with Agentic AI, LLM platforms, and orchestration frameworks.
- Proficiency in Python, APIs, Kubernetes, Docker, and cloud platforms (Azure preferred).
- Knowledge of AI governance, security, compliance, and observability best practices.
- Strong problem-solving, architecture, and communication skills.
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