AI Platform Engineer (AI)

Location: Boston, Massachusetts; Springfield, Massachusetts; or New York, New York

Salary: $163,900–$215,000 per year

Company

hirify.global is a large insurance and financial services company operating an AI Platform Engineering team that builds foundational capabilities for enterprise AI initiatives.

What you will do

• Define architectural direction and roadmaps for cloud infrastructure, AI serving layers, developer tooling, and platform reliability.
• Lead the design of critical platform components, including LLM gateways, multi-tenant compute isolation, model-serving infrastructure, and enterprise integrations.
• Own complex platform initiatives from scoping and sequencing through production, managing technical risk and quality.
• Define SLOs, improve observability, lead incident reviews, and raise platform stability and operational maturity.
• Design governance and compliance controls covering data residency, access management, audit logging, and AI usage policies.
• Drive alignment across AI engineering, product, and cloud engineering teams while mentoring engineers through design reviews, documentation, and hands-on pairing.

Requirements

• At least 5 years of experience in platform engineering, infrastructure, or SRE, with technical leadership or staff-level individual contributor scope.
• At least 3 years of experience in cloud-native architecture, including Kubernetes at scale, managed cloud services, networking, identity federation, and multi-tenancy across AWS, GCP, or Azure.
• At least 3 years of owning complex, multi-month platform initiatives from initial design through production.
• Certified Kubernetes Administrator, Certified Kubernetes Application Developer, or equivalent AWS certification.
• Experience with infrastructure as code and GitOps, such as Terraform or Pulumi and ArgoCD.
• Experience with AI/ML infrastructure, model serving, inference pipelines, GPU resource management, or LLM integration patterns.

Nice to have

• Experience with vLLM, Triton, Ray Serve, AI gateway design, or LLM serving at scale.
• Experience building an internal developer platform from scratch and improving internal developer experience.
• Knowledge of AI safety, model evaluation, governance frameworks, FinOps, or GPU cost optimization.
• Open-source contributions to platform or ML infrastructure tooling.

Culture & Benefits

• Peer learning, candid feedback, shared technical standards, and a focus on engineering excellence.
• Regular meetings with the AI Platform Engineering team and focused one-on-one meetings with a manager.
• Access to employee Business Resource Groups and learning content through Degreed and other platforms.
• Industry-leading pay and benefits within a stable, ethics-focused organization.