AI Engineer
Job in
Dearborn, Wayne County, Michigan, 48124, USA
Listed on 2026-07-27
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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.
- 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.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
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