W2 contract || AI Gateway Engineer- Platform & Identity Access Management (IAM)

Job Title: AI Gateway Engineer- Platform & Identity Access Management (IAM)

Job Location: Milpitas, CA (Onsite from day one)

Job Duration: 6+ months

Minimum years of experience required: 7+ years

Type of Hire: w2 contract

JOB DETAILS:

We are seeking an experienced AI Gateway Engineer to design, implement, secure, and operate enterprise AI Gateway platforms that enable governed access to Large Language Models (LLMs), AI agents, foundation models, and AI services across hybrid and cloud environments.

The ideal candidate will have strong expertise in AI Platforms, API Gateways, IAM, OAuth/OIDC, Enterprise Security, AI Governance, Kubernetes, and Cloud Architecture, ensuring secure, scalable, and compliant AI consumption across the organization. The role will focus on AI traffic management, model access control, agent security, policy enforcement, observability, and responsible AI controls.

Key Responsibilities

AI Gateway Platform Engineering

Design and implement enterprise AI Gateway platforms for GenAI, Agentic AI, and LLM workloads.

Build and manage centralized ingress and egress gateways for AI applications, agents, MCP servers, and external AI services.

Develop AI traffic routing, model orchestration, load balancing, failover, and request governance capabilities.

Implement model abstraction layers supporting multiple AI providers including OpenAI, Azure OpenAI, Anthropic, Google Gemini, AWS Bedrock, and private models.

Design multi-tenant AI platform architectures for enterprise consumption.

Establish AI service onboarding standards and platform governance processes.

Identity & Access Management (IAM)

Design AI-specific authentication and authorization frameworks.

Implement OAuth2, OpenID Connect (OIDC), SAML, JWT, API keys, and service-account-based access controls.

Configure RBAC and ABAC policies for AI applications and agents.

Integrate AI platforms with:

o Microsoft Entra ID (Azure AD)

o Okta

o Ping Identity

o CyberArk

o AWS IAM

o Google Cloud IAM

Design least-privilege access models for agents, tools, and AI services.

Implement agent identity and machine-to-machine authentication mechanisms.

Manage secret handling, token lifecycle, certificate rotation, and privileged access controls.

AI Security & Governance

Implement enterprise AI Guardrails and Responsible AI controls.

Configure protections for:

o Prompt Injection

o Jailbreak Attacks

o Malicious URL Detection

o Data Leakage Prevention

o Sensitive Data Masking

o PII Detection

o Content Moderation

Design AI security policies using Policy-as-Code and Governance-as-Code methodologies.

Establish model access governance, agent authorization, and inference authorization mechanisms.

Support compliance frameworks including:

o NIST AI RMF

o NIST CSF

o ISO 27001

o SOC2

o GDPR

o HIPAA

Conduct AI threat modeling and risk assessments.

Cloud & Platform Engineering

Build and manage AI platform infrastructure on:

o Azure

o AWS

o Google Cloud Platform

Deploy and manage Kubernetes-based AI environments.

Develop Infrastructure as Code using:

o Terraform

o CloudFormation

o Helm

Automate AI platform provisioning and governance controls.

Implement CI/CD pipelines for AI platform deployment and policy validation.

Support highly available and scalable AI runtime environments.

Observability & Monitoring

Implement AI platform observability frameworks.

Monitor:

o Model utilization

o Latency

o Cost

o Token Consumption

o Security Violations

o Agent Activities

Build dashboards using:

o Grafana

o Prometheus

o Splunk

o Datadog

o Azure Monitor

o CloudWatch

Develop audit and compliance reporting mechanisms.

Establish AI operational metrics and SLOs.

DevSecOps & Automation

Integrate security controls into AI delivery pipelines.

Implement:

o SAST

o DAST

o SCA

o Container Security

o IaC Security Validation

Automate AI policy enforcement and compliance checks.

Support software supply chain security and AI BOM/SBOM validation.

Build reusable platform automation frameworks and reference architectures.

Required Qualifications

Education

Bachelor's or Master's degree in:

o Computer Science

o Information Technology

o Engineering

o Cybersecurity

o Related discipline

Experience

7+ years in Platform Engineering, Cloud Engineering, Security Engineering, or IAM.

3+ years in AI/GenAI platform implementation.

Experience deploying enterprise AI solutions in production environments.

Strong exposure to secure software development and cloud-native architectures.

Technical Skills

AI Technologies

Large Language Models (LLMs)

RAG Architectures

AI Agents

MCP Frameworks

Prompt Engineering

Vector Databases

AI Gateway Platforms

AI Guardrails

Model Governance

IAM & Security

OAuth2

OIDC

SAML

JWT

RBAC

ABAC

Zero Trust Architecture

PAM Solutions

Secrets Management

Cloud Platforms

Azure

AWS

GCP

Cloud IAM Services

Microsoft Entra ID

AWS IAM

Google Cloud IAM

Okta

PingFederate

CyberArk

DevOps & Platform

Kubernetes

Docker

Terraform

Helm

GitHub Actions

Azure DevOps

Jenkins

Programming

Python

Go

Java

PowerShell

Shell Scripting

Preferred Certifications

AI & Cloud

Microsoft Certified: Azure AI Engineer Associate

Google Professional Cloud AI Engineer

AWS Machine Learning Specialty

Microsoft AI Engineer

IAM & Security

CISSP

CCSP

Certified Identity & Access Manager (CIAM)

CyberArk Defender/Sentry

Platform & Cloud

Certified Kubernetes Administrator (CKA)

Terraform Associate

AWS Solutions Architect Professional

Azure Solutions Architect Expert

Key Competencies

Enterprise Architecture

AI Governance

Platform Engineering

Security Design

Identity Architecture

Stakeholder Management

Problem Solving

Automation Mindset

Risk Assessment

Technical Leadership