AI Platform Engineer (AI)

TL;DR

AI Platform Engineer (AI Infrastructure): Building and operating the platform powering AI initiatives with an accent on LLM gateways, multi-tenant compute isolation, and model serving infrastructure. Focus on designing architectural standards via ADRs, managing technical risk for major initiatives, and implementing enterprise governance and compliance controls.

Location: Must be based in Boston, Springfield, or New York, USA

Salary: $163,900–$215,000

Company

hirify.global is a large financial services corporation providing insurance and investment solutions.

What you will do

• Define architectural direction for AI platform components, including cloud infrastructure, serving layers, and reliability strategy.
• Lead the design and deployment of critical components like LLM gateways, multi-tenant compute isolation, and model serving infrastructure.
• Establish team engineering standards by writing Architecture Decision Records (ADRs) and leading design reviews.
• Own the end-to-end technical execution of major platform initiatives, from scoping and sequencing to production.
• Develop platform reliability strategies, including the definition of SLOs and observability frameworks.
• Design and implement technical governance and compliance controls for data residency and AI usage policies.

Requirements

• 5+ years of experience in platform engineering, infrastructure, or SRE, with a track record as a technical lead.
• 3+ years of experience in cloud-native architecture, including Kubernetes at scale across AWS, GCP, or Azure.
• 3+ years of proven ownership of complex, multi-month platform initiatives from concept to production.
• Certification as a Kubernetes Administrator (CKA), Application Developer (CKAD), or equivalent AWS certifications.
• Must be located in or able to work from Boston, Springfield, or New York.

Nice to have

• Fluency in Infrastructure as Code (Terraform, Pulumi) and GitOps (ArgoCD).
• Hands-on experience with AI/ML infrastructure, such as vLLM, Triton, or Ray Serve.
• Experience building Internal Developer Platforms (IDP) with a product-centric mindset.
• Knowledge of AI safety, model evaluation, and GPU cost optimization (FinOps).
• Contributions to open-source platform or ML infrastructure tooling.

Culture & Benefits

• Access to diverse Business Resource Groups (Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused).
• Learning and development opportunities via Degreed and other informational platforms.
• Industry-leading pay and benefits package within a stable ethical business.
• Culture of peer learning, candid feedback, and shared technical standards.