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AI Platform Architect
Job in
Hackensack, Bergen County, New Jersey, 07601, USA
Listed on 2026-02-19
Listing for:
The University of Texas MD Anderson Cancer Center
Full Time
position Listed on 2026-02-19
Job specializations:
-
Software Development
AI Engineer
Job Description & How to Apply Below
Job Title:AI Platform Architect
Job Number: 37266
Location: ,NJ
Job DescriptionOur client is looking for an AI Platform Architect to design, build, and scale their end-to-end AI platform. This role sits at the intersection of cloud infrastructure, machine learning, backend APIs, and frontend enablement. You will own the architecture that takes data from ingestion all the way to production-grade AI experiences.
ResponsibilitiesPlatform & Architecture
- Design and own the end-to-end AI platform architecture across AWS, Databricks, APIs, and frontend consumers
- Define standards for data ingestion, feature engineering, model training, serving, and monitoring
ML & Data Platform
- Lead architecture and best practices for Databricks on AWS Implement data pipelines using Delta Lake (Bronze/Silver/Gold)
- Own MLflow setup for experiment tracking, model registry, and lifecycle management
Backend & API Layer
- Design and build production-grade APIs using FastAPI
- Define API contracts and integration patterns for frontend and downstream systems
- Implement authentication, authorization, rate limiting, caching, and observability
Frontend Enablement
- Collaborate with frontend teams (React / Next.js) to deliver AI-powered user experiences
- Define API schemas and response patterns optimized for UI consumption
MLOps & Dev Ops
- Establish CI/CD pipelines for models, APIs, and infrastructure
- Enable safe deployments (blue/green, canary, rollback)
Security & Governance
- Ensure secure handling of PII and sensitive data
- Implement IAM best practices and secrets management
- 7+ years of experience in software, data, or platform engineering
- 3+ years designing or operating ML/AI platforms in production
- Strong experience with AWS (S3, IAM, ECS/EKS, Lambda, API Gateway, Cloud Watch)
- Hands-on experience with Databricks, Delta Lake, and MLflow
- Strong Python skills and production experience with FastAPI
- Experience deploying and operating scalable APIs
- Experience with LLMs / GenAI platforms
- Terraform or AWS CDK experience
- Streaming data (Kafka, Kinesis)
- Feature stores and real-time ML systems
- Observability tools (Prometheus, Open Telemetry)
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