Senior Solution Architect – AI Technologies

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

Title: Senior Solution Architect – AI Technologies

Experience: 15-20 Years

We are seeking an experienced Solution Architect – AI Technologies with 15-20 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

• 15-20 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.