
AI Infrastructure Architect
1101 GREENWOOD · HybridJob$166–254K/yrSeen 3 days agoSeen in employer's feed 3 days ago
Most applications go out cold — see where you stand first. No sign-up to start.
Watch jobs like this. New roles like this one near 1101 GREENWOOD, by email.
Don't just apply. Show up ready.
Olive works from this exact posting.
At a glance
Olive lists jobs from US employers, including remote roles you can work from the United States.
Job overview
The AI Infrastructure Architect provides strategic oversight and planning for enterprise infrastructure and AI platform initiatives, designs and builds platform engineering constructs, defines target-state and reference architectures, evaluates emerging technologies, ensures compliance and security, and partners with engineering teams to deliver scalable, secure, and cost‑effective solutions.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Duties & Responsibilities:
-
Serves as the key infrastructure architecture influencer providing strategic oversight and planning for enterprise infrastructure and AI platform initiatives.
-
Design and build Platform Engineering constructs enabling CI/CD, and governance for AI Platform consumers
-
Defines target-state architecture, reference architectures, reusable platform patterns, frameworks, and solution blueprints for AI-enabled infrastructure capabilities.
-
Provides architecture guidance for AWS-first AI platform capabilities, while evaluating when other cloud providers, SaaS platforms, or specialized third-party technologies may be appropriate.
-
Evaluates emerging technologies including AWS AgentCore, Workato, TrueFoundry, AI gateways, LLM platforms, agentic frameworks, RAG, embeddings, policy enforcement, observability, and workflow orchestration tools.
-
Develops and reviews solutions to ensure infrastructure systems, AI platform capabilities, and associated processes align with IT strategy, security expectations, compliance requirements, and operational standards.
-
Partners with I&O engineering teams to define platform design, support requirements, operational guardrails, implementation patterns, and handoff expectations.
-
Designs infrastructure patterns that support AI platform integration with enterprise systems of record, APIs, event-driven architectures, data platforms, identity systems, secrets management, observability platforms, and IT service management processes.
-
Ensures platform designs intentionally account for regulated-environment requirements, including data protection, access control, auditability, PHI/PII handling, resiliency, vendor risk, and compliance-by-design.
-
Identifies architectural risks, technical debt, scalability concerns, compliance gaps, vendor lock-in risks, cost-management issues, and operational support limitations in proposed platform designs.
-
Leads or participates in proofs of concept, sandbox validation, and early Dev-environment architecture validation before transitioning implementation responsibility to engineering delivery teams.
-
Produces component specifications, candidate architectures, roadmaps, policies, standards, and practices that support consistent, compliant, and extensible infrastructure and AI platform delivery.
-
Defines observability, capacity, performance, and cost-management patterns across traditional, cloud-native, and AI-enabled platforms.
-
Presents architecture recommendations to senior IT leaders and influences application, infrastructure, and platform decisions without direct management authority.
Minimum Qualifications :
-
Technical degree or equivalent work experience with a high school diploma or a GED from an accredited institution
-
7+ years of enterprise infrastructure, cloud, or platform architecture experience, including 5+ years leading architecture for scalable, resilient, secure, and operationally supportable platforms.
-
Strong AWS-first cloud architecture experience, including compute, networking, IAM, DNS, storage, serverless, observability, security controls, infrastructure as code, platform engineering, and automated delivery patterns.
-
Experience evaluating emerging AI, automation, data, integration, or platform technologies through experimentation, vendor engagement, and structured technical assessment.
-
Experience designing secure, compliant, auditable, resilient, and cost-conscious platforms in a highly regulated environment such as healthcare, financial services, insurance, or another compliance-sensitive industry.
-
Hands-on ability to validate architecture decisions through sandbox experimentation, proofs of concept, cloud configuration, and scripting/automation.
-
Experience influencing engineering, product, application, and senior IT stakeholders without direct management authority.
-
Experience implementing cloud services using infrastructure as code tools such as Terraform, CloudFormation, Ansible, or equivalent.
Preferred Qualifications :
-
AWS Solutions Architect Professional certification or equivalent AWS architecture experience.
-
Experience with AI platform architecture and AWS AI/ML services, including agentic automation, LLM integration, RAG, embeddings, AI gateways, model orchestration, AWS AgentCore, Amazon Bedrock, or related platform services.
-
Experience with workflow automation or enterprise integration platforms such as Workato, MuleSoft, Boomi, ServiceNow IntegrationHub, or similar.
-
Experience with AI platform, MLOps, or LLMOps technologies such as TrueFoundry, vector databases, model gateways, prompt management, evaluation tooling, or policy enforcement layers.
-
Experience designing secure integration patterns between AI platforms and enterprise systems of record, APIs, event buses, data platforms, and identity providers.
-
Experience with API gateway, service mesh, or traffic-management platforms such as Kong, Apigee, NGINX, Istio, or equivalent.
-
Experience with observability platforms and practices, including logging, metrics, tracing, audit trails, runtime telemetry, cost analytics, and production-readiness dashboards.
-
Experience with Kubernetes, containers, serverless platforms, GPU/accelerated compute, self-hosted model evaluation, managed model platforms, or hybrid AI runtime patterns.
-
Experience working with development teams to design cloud-native applications and platform capabilities.
Compliance & Regulatory Responsibilities: N/A
License/Certification: N/A
Hiring Range*:
Greater New York City Area (NY, NJ, CT residents): $165,900 - $253,810
All Other Locations (within approved locations): $141,700 - $216,835
As a candidate for this position, your salary and related elements of compensation will be contingent upon your work experience, education, licenses and certifications, and any other factors Healthfirst deems pertinent to the hiring decision.
In addition to your salary, Healthfirst offers employees a full range of benefits such as, medical, dental and vision coverage, incentive and recognition programs, life insurance, and 401k contributions (all benefits are subject to eligibility requirements). Healthfirst believes in providing a competitive compensation and benefits package wherever its employees work and live.
*The hiring range is defined as the lowest and highest salaries that Healthfirst in “good faith” would pay to a new hire, or for a job promotion, or transfer into this role.
WE ARE AN EQUAL OPPORTUNITY EMPLOYER. Applicants and employees are considered for positions and are evaluated without regard to mental or physical disability, race, color, religion, gender, gender identity, sexual orientation, national origin, age, genetic information, military or veteran status, marital status, mental or physical disability or any other protected Federal, State/Province or Local status unrelated to the performance of the work involved.
You've read the whole posting — now see how you match it.