Senior Solution Architect - AI Technologies
Dearborn MI
Full Time
Position Summary
Experience: 15 Years
We are seeking an experienced Solution Architect - AI Technologies with 15 years of overall IT experience and deep expertise in designing, architecting, and delivering enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will possess strong technical leadership skills, hands-on experience with modern AI frameworks, and the ability to translate business requirements into scalable AI-driven solutions.
This role requires expertise in Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, Multi-Agent Systems, LangGraph, Model Context Protocol (MCP), Large Language Models (LLMs), Python, PySpark, Cloud AI Services, and Enterprise Data Platforms.
Key Responsibilities
- Define and lead enterprise AI architecture strategy aligned with business objectives.
- Design scalable and secure AI/GenAI solutions leveraging LLMs, RAG frameworks, and Agentic AI architectures.
- Create end-to-end solution blueprints covering data ingestion, knowledge retrieval, orchestration, model interaction, observability, and governance.
- Develop architecture roadmaps for AI modernization initiatives.
Generative AI & Agentic AI
- Design and implement enterprise-scale RAG systems using vector databases and semantic search technologies.
- Architect multi-agent and autonomous agent workflows using frameworks such as LangGraph and Agentic AI platforms.
- Develop AI solutions utilizing MCP (Model Context Protocol) for tool integration and contextual orchestration.
- Establish best practices for prompt engineering, agent collaboration, memory management, and workflow orchestration.
- Drive adoption of AI-powered automation and intelligent decision-making systems.
Data & Engineering Leadership
- Design scalable data pipelines using Python, PySpark, and cloud-native technologies.
- Architect enterprise knowledge management solutions supporting AI applications.
- Define data governance, security, privacy, and compliance frameworks for AI systems.
- Collaborate with data engineering teams to optimize AI data platforms.
- Architect AI solutions on GCP cloud platforms.
- Evaluate and integrate AI services, vector databases, model serving platforms, and observability tools.
- Ensure scalability, reliability, performance, and cost optimization of AI solutions.
- Drive MLOps and LLMOps adoption across development teams.
Stakeholder Management
- Engage with business stakeholders, product owners, and leadership teams to define AI strategy and roadmap.
- Conduct solution workshops, architecture reviews, and technical governance sessions.
- Mentor architects, developers, and AI engineers on enterprise AI best practices.
- Support presales activities, client presentations, and AI transformation initiatives.
Required Skills & Qualifications
Experience
- 15 years of overall IT experience.
- Minimum 5+ years in AI/ML and Generative AI solution architecture.
- Proven experience leading enterprise-scale architecture programs.
AI & GenAI Technologies
- Strong expertise in:
- Generative AI
- Retrieval-Augmented Generation (RAG)
- Agentic AI Systems
- LangGraph
- LangChain
- AI Orchestration Frameworks
- Prompt Engineering
- Expert-level proficiency in Python.
- Strong hands-on experience with PySpark.
- Experience with distributed data processing and analytics platforms.
- Knowledge of data modeling, ETL, and data governance.
AI Infrastructure & Platforms
- Experience with:
- Knowledge Graphs
- LLMOps/MLOps Platforms
- AI Monitoring and Evaluation Frameworks
- API Design and Microservices Architecture
- Strong experience in Azure, AWS, or Google Cloud Platform.
- Knowledge of cloud-native AI services and enterprise deployment patterns.
Preferred Qualifications
- Experience in Automotive, Manufacturing, Supply Chain, or Engineering domains.
- Exposure to enterprise platforms such as PLM or Digital Engineering ecosystems.
- Experience implementing AI governance, responsible AI, and security frameworks.
- AI/Cloud certifications from Google Cloud.
- Lead technical architecture reviews and solution decisions.
- Provide thought leadership on emerging AI technologies and industry trends.
- Drive innovation initiatives leveraging GenAI and Agentic AI capabilities.
- Mentor and guide cross-functional teams in AI solution delivery.