Principal AI Engineer

Judge Group, Inc.

Detroit (MI)

Hybrid

USD 124,000 - 138,000

Full time

3 days ago

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Benefits offered by this job

Health insurance

Job summary

Judge Group, Inc. is seeking an experienced AI Architect / Principal AI Engineer to design and build enterprise-scale AI platforms and developer tools. You will lead architecture, integration, and operationalization of AI-powered systems across the organization, driving governance, security, and observability.

The role requires deep hands-on experience with Gemini, Vertex AI, Google Cloud AI services, Java Spring Boot, and React.js, plus mentoring teams and defining platform strategy.

Qualifications

Bachelor’s degree or equivalent practical experience.
7+ years in software/AI engineering or related fields.
Proven success delivering production-grade AI, LLM, or developer platform solutions.
Hands-on with Gemini, Vertex AI, and GCP AI services.
Strong expertise in AI agent architectures and multi-agent systems.
Experience with Java, Spring Boot, REST APIs, and microservices.
Experience with React.js and modern web development.
Knowledge of OAuth 2.0, OIDC, API security.

Responsibilities

Architect and lead enterprise AI platform development.
Design reusable AI services and reference architectures.
Drive AI initiatives using Google Cloud, Gemini, Vertex AI, and GitHub Copilot.
Build secure, scalable AI solutions integrated with enterprise security.
Establish AI governance, privacy, and model risk management.
Implement observability with logging, monitoring, and dashboards.
Collaborate with stakeholders to shape AI strategy and roadmap.
Mentor engineers on AI architecture and platform adoption.
Lead continuous improvement across tooling and developer experience.
Influence enterprise-wide AI architecture standards.

Skills

AI architecture

Cloud platforms

Software engineering

Security & governance

DevOps

Education

Bachelor’s degree in Computer Science, Engineering, AI, or related field

Tools

Gemini

Vertex AI

Google Cloud Platform AI services

Java Spring Boot

React.js

OAuth 2.0

OIDC

CI/CD

Harness

Azure DevOps

LangChain

LangChain4j

MCP Servers

Model Garden

Model Runtime

Model Gateway

Agent Gateway

Google ADK

Spring AI

GitHub Copilot

Job description

Location: Detroit, MI Salary: $90.00 USD Hourly – $100.00 USD Hourly Description:

Location: Open Across Footprints (4 Days Onsite, 1 Day Remote)
Duration: November 2, 2026 – February 9, 2027
Employment Type: Contract-to-Hire

About the Role

We are seeking an experienced AI Architect / Principal AI Engineer to join our Engineering Frameworks Team. This is a strategic, hands-on leadership role focused on designing and building enterprise-scale AI platforms, developer tools, and agentic AI solutions that enable engineering teams across the organization to innovate faster.

You will lead the architecture, development, integration, and operationalization of AI-powered platforms leveraging technologies such as Google Cloud Platform (Google Cloud Platform), Gemini, Vertex AI, Claude Code, GitHub Copilot, MCP Servers, Java Spring Boot, and React.js . The ideal candidate has deep experience delivering production-grade AI solutions and building scalable frameworks that empower development teams to create intelligent applications and custom AI agents.

What You’ll Do

Architect and lead the development of enterprise AI platforms, agent frameworks, and developer productivity solutions.
Design reusable AI services, orchestration patterns, integration frameworks, and reference architectures for enterprise adoption.
Drive AI initiatives leveraging Google Cloud Platform, Gemini, Vertex AI, Claude Code, GitHub Copilot, MCP Servers, and emerging agentic technologies.
Build and operationalize secure, scalable, and reliable AI solutions integrated with enterprise cloud and security platforms.
Establish best practices for AI governance, responsible AI, privacy, security, access control, and model risk management.
Implement observability frameworks, including logging, monitoring, tracing, token utilization tracking, and operational dashboards.
Collaborate with product management, security, architecture, and business stakeholders to define AI platform strategy and roadmap.
Mentor engineers and technical teams on AI architecture, platform adoption, and custom agent development.
Drive continuous improvement across platform engineering, AI tooling, and developer experience initiatives.
Lead technical decision-making and influence enterprise-wide AI architecture standards.

Required Qualifications

Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field, or equivalent practical experience.
7 years of experience in software engineering, platform engineering, AI engineering, or related technical disciplines.
Proven success delivering production-grade AI, LLM, or developer platform solutions.
Hands-on experience with Gemini, Vertex AI, Google Cloud Platform AI services, or comparable cloud AI platforms.
Strong expertise in AI agent architectures, agent orchestration, workflow automation, and multi-agent systems.
Extensive experience developing enterprise applications using Java, Spring Boot, REST APIs, and Microservices.
Experience with React.js and modern web application development.
Strong understanding of OAuth 2.0, OpenID Connect (OIDC), API security, authentication, and authorization frameworks.
Experience with CI/CD, cloud-native development, observability, application reliability, and software delivery best practices.
Strong problem-solving skills and ability to lead highly technical initiatives.

Preferred Qualifications

Experience using Claude Code and GitHub Copilot within software development workflows.
Experience building or integrating MCP (Model Context Protocol) Servers and Clients.
Experience with Agent-to-Agent (A2A) communication frameworks and distributed agent ecosystems.
Hands-on experience with Google ADK, Spring AI, LangChain, LangChain4j, or similar AI frameworks.
Experience working with Gemini Agent Platform and Vertex AI capabilities, including Model Garden, Model Runtime, Model Gateway, and Agent Gateway.
Familiarity with AI governance frameworks, Google Cloud Platform Model Armor, token controls, rate limiting, and AI cost management.
Experience designing monitoring solutions for AI workloads, including observability, tracing, and performance analytics.
Experience with containerization technologies and cloud-native architecture patterns.
Experience building CI/CD pipelines using Harness and Azure DevOps.
Experience working within Agile and Scrum environments.