Senior Generative AI Solutions Architect (Enterprise)

Pentangle Tech Services | P5 Group; Dearborn (MI); On-site; USD 180,000 - 240,000; Full time

Job summary

Pentangle Tech Services | P5 Group is seeking an experienced Senior Solution Architect – AI Technologies to lead enterprise AI architecture efforts. The role focuses on designing and delivering Generative AI, RAG, and Agentic AI solutions across data ingestion, retrieval, orchestration, and governance, with leadership across engineering teams.

The candidate will drive MLOps/LMLops, ensure scalable data pipelines using Python and PySpark, and collaborate with stakeholders to translate business

Qualifications

• 15-20 years of overall IT experience.
• Minimum 5+ years in AI/ML and Generative AI solution architecture.
• Proven experience leading enterprise-scale architecture programs.

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.
• Design scalable data pipelines using Python, PySpark, and cloud-native technologies.
• Architect enterprise knowledge management solutions for AI applications.
• Define data governance, security, privacy, and compliance frameworks for AI systems.

Skills

Generative AI

LLMs

Python

PySpark

LangGraph

LangChain

AI Orchestration

Prompt Engineering

Cloud platforms

MLOps

Tools

LangGraph

LangChain

PySpark

Job description

Pentangle Tech Services | P5 Group is seeking an experienced Senior Solution Architect – AI Technologies to lead enterprise AI architecture efforts. The role focuses on designing and delivering Generative AI, RAG, and Agentic AI solutions across data ingestion, retrieval, orchestration, and governance, with leadership across engineering teams.

The candidate will drive MLOps/LMLops, ensure scalable data pipelines using Python and PySpark, and collaborate with stakeholders to translate business