Principal Engineer - AI Platform Architecture & Scale

Principal Engineer - AI Platform Architecture & Scale

Contract Details:

Title: Principal Engineer – AI Platform Architecture & Scale

Location: New York, NY - Remote with occasional travel Duration: 6+ month Contract/C2H

Start Date: ASAP

Candidates Considered: USC or GC Holder

Overview

We are seeking a Principal Engineer to own the architecture, scalability, and governance of enterprise AI/ML systems. This role is focused on ensuring the stability, security, and efficiency of production AI platforms, enabling innovation at scale across the organization. The ideal candidate is a systems-oriented engineer who thrives on building resilient, observable, and cost-efficient AI infrastructure.

Key Responsibilities

• Provide primary oversight of AI/ML platforms and supporting infrastructure, ensuring performance, scalability, and reliability across environments.
• Serve as the primary point of oversight for third-party vendors and service providers, managing deliverables, SLAs, and integration with internal systems.
• Lead design and implementation of scalable AI/ML platform architecture, ensuring high performance and security.
• Translate AI/ML prototypes into production-ready systems integrated with enterprise data and cloud environments.
• Architect and optimize feature and model-serving pipelines (batch, streaming, real-time) using AWS Bedrock, ECS, and Lambda.
• Oversee CI/CD, automated testing, monitoring, and governance for multi-team AI delivery.
• Partner with Science and DevOps teams to support continuous integration and deployment of ML models.
• Ensure adherence to data privacy, compliance, and security standards.
• Collaborate with cross-functional engineering teams and third-party partners to drive platform excellence.

Required Skills & Experience

• High proficiency in Zero Trust and Defense in Depth security principles and frameworks
• Deep understanding of secure API gateway design, enterprise security architecture patterns, and LLM (Large Language Model) governance frameworks.
• 7+ years of software engineering experience with strong exposure to ML/AI systems.
• Proven success in architecting secure, cloud-native AI platforms (AWS preferred).
• Deep experience with MLOps tools, CI/CD automation, Docker, Kubernetes, Terraform.
• Expertise in observability and system reliability engineering for ML systems.
• Proficiency in Python, distributed systems, and event-driven architecture.
• Experience managing vendor engineering pods or offshore partners preferred.
• Background in life sciences, wellness, or regulated environments is a plus.