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AI Engineer

Job in Dearborn, Wayne County, Michigan, 48124, USA
Listing for: Apex Systems
Full Time position
Listed on 2026-07-27
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, Machine Learning/ ML Engineer
Job Description & How to Apply Below

AI Platform Engineer

We are seeking a Senior AI Platform Engineer to design, build, and scale next-generation AI solutions for an Enterprise Data Platform on Google Cloud Platform (GCP). This is a highly technical, hands-on individual contributor role focused on developing production-grade multi-agent AI systems, AI-powered workflows, and developer-facing capabilities.

The ideal candidate will combine deep software engineering expertise with practical experience building and operating LLM-based applications in production environments. This role requires ownership of solution architecture, hands-on development, technical leadership, and cross-functional collaboration to deliver scalable, secure, and observable AI solutions.

Key Responsibilities
  • Design and implement multi-agent AI systems and agent orchestration frameworks.
  • Evaluate architectural trade-offs, including:
    Single-agent vs. multi-agent architectures, Retrieval-Augmented Generation (RAG) vs. fine-tuning approaches, Agent workflow design and orchestration strategies.
  • Contribute to Architecture Decision Records (ADRs) and technical design documentation.
  • Define scalable, secure, and maintainable AI platform patterns.
AI Application Development
  • Develop and deploy production-grade AI applications and agentic workflows.
  • Build solutions supporting:
    Natural Language to SQL (NL-to-SQL), Semantic search, Metadata enrichment, Intelligent automation workflows.
  • Implement AI guardrails, observability, monitoring, and evaluation frameworks.
  • Leverage modern agent development tools and coding assistants.
Full-Stack Engineering
  • Develop backend services using:
    Python, FastAPI.
  • Build frontend experiences using:
    Angular, React.
  • Create chat interfaces, APIs, developer tooling, and user-facing AI experiences.
  • Own end-to-end feature delivery from design through production deployment.
Engineering Excellence
  • Write high-quality, maintainable, and testable code.
  • Lead technical reviews and establish engineering best practices.
  • Perform root-cause analysis and troubleshoot complex AI agent failures.
  • Serve as the team's technical expert for advanced AI and platform engineering challenges.
  • Drive continuous improvements in reliability, scalability, and performance.
Collaboration & Leadership
  • Partner closely with Product Management, Data Engineering, and Platform Engineering teams.
  • Participate in sprint planning, backlog refinement, and technical roadmap discussions.
  • Mentor team members and promote knowledge sharing.
  • Support onboarding and technical development of new engineers.
Required Qualifications
  • 5+ years of professional software engineering experience.
  • Demonstrated hands-on coding expertise with modern application development practices.
  • Experience building and operating AI-powered applications or LLM-based systems in production environments.
  • Ability to interpret ambiguous business requirements and independently deliver robust, well-tested solutions.
  • Experience designing scalable cloud-native applications.
Technical Skills
  • Artificial Intelligence and Expert Systems
  • Large Language Models (LLMs)
  • Agent-based AI architectures
  • API development and microservices
  • Python development
  • FastAPI
  • Frontend development using Angular or React
  • Production software engineering and Dev Ops practices
Agentic AI Experience
  • Experience building agent-based systems using frameworks such as:
    Google Agent Development Kit (ADK), CrewAI, Lang Graph, Similar agent orchestration platforms.
  • Familiarity with agentic development tools and AI-assisted coding environments, including:
    Open Code, Claude code, Comparable AI developer productivity tools.
Preferred Qualifications
  • Cloud & Platform Experience
  • Google Cloud Platform (GCP)
  • Cloud-native application architecture
  • Platform engineering and AI infrastructure
  • Machine Learning & AI
  • Applied machine learning experience, including:
    Embeddings, Classification, Clustering, Natural Language Processing (NLP), Model evaluation and benchmarking.
  • Experience implementing AI evaluation frameworks and quality metrics.
  • Data & Governance
  • Familiarity with:
    Data engineering principles, Enterprise data platforms, Metadata management, Data governance processes.
Education
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
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