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# Technical Architect Agentic AI / Data & ML

- **Company:** Intellisoft Inc
- **Location:** Seattle, WA, United States
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Data Cleansing, Software Design Documents, Python (Programming Language), Machine Learning, Natural Language Processing, Systems Development Life Cycle, Power BI, OpenAI, Azure Machine Learning, Runbook, Software Deployment, Explainable AI (XAI), Google Cloud, Azure Data Factory, LangChain, Retrieval-Augmented Generation, Large Language Models, SHAP (Shapley Additive Explanations), Multi-Agent Systems, Deep Learning, Multi-Cloud, Generative AI, Agentic-AI, Microsoft Fabric, AI Platforms, Pyspark, Scikit Learn, Machine Learning Operations, Graph RAG, Azure Synapse Analytics, Unsupervised Learning, Databricks
- **Published:** September 30, 2026
- **Apply:** https://www.dice.com/job-detail/fd1e2690-728c-4b7b-aeae-811b1ab2d430

## About the Role

We are seeking an experienced Technical Architect with 15+ years of experience in Data, AI, ML Engineering, and enterprise architecture. The ideal candidate will have strong expertise in the Azure Data & AI ecosystem, along with hands-on experience designing Agentic AI, GenAI, ML, RAG, and multi-cloud solutions., * 15+ years of experience in Data/AI/ML Engineering, Architecture, or related technology domains.

 * Strong expertise in the Azure Data & AI stack with working knowledge of AWS and Google Cloud Platform.
 * Hands-on experience with Python, PySpark, Azure ML, Databricks, and Scikit-learn.
 * Strong experience with LangChain, LangGraph, Agentic AI, LLMs, embeddings, RAG, and GraphRAG.
 * Experience with vector databases and AI/ML workflow orchestration.
 * Strong understanding of MLOps, LLMOps, CI/CD, SDLC, and enterprise AI deployment.
 * Experience with ML techniques including supervised/unsupervised learning, forecasting, NLP, and deep learning.
 * Experience implementing Explainable AI (XAI) using SHAP, LIME, fairness, and transparency techniques.
 * Strong exposure to Azure Synapse, Microsoft Fabric, Azure Data Factory, Databricks, and Power BI.
 * Experience designing secure and scalable enterprise Data/AI platforms.
 * Proven experience with RFP/RFI responses, client solutioning, technical proposals, and architecture workshops.
 * Strong communication, stakeholder management, architecture, and mentoring skills

## Description

* Architect Agentic AI solutions using Azure OpenAI, LangChain, LangGraph, and multi-agent frameworks.
 * Build RAG pipelines, vector database integrations, embeddings, GraphRAG, and autonomous workflow orchestration.
 * Lead the complete ML lifecycle, including data preparation, modeling, training, evaluation, deployment, and MLOps.
 * Govern the full SDLC for Data, ML, and GenAI platforms.
 * Implement Explainable AI (XAI) using technologies such as SHAP and LIME, including fairness and transparency models.
 * Architect and deploy solutions across Azure, AWS, and Google Cloud Platform.
 * Drive RFP/RFI responses, technical proposals, estimations, solutioning, and client workshops.
 * Ensure solutions meet security, compliance, privacy, and governance requirements, including GDPR, CCPA, and PII protection.
 * Create architecture blueprints, ML design documents, technical roadmaps, and runbooks.
 * Engage with business and IT stakeholders to understand business challenges, priorities, success metrics, and technical risks.
 * Design secure, scalable Data and AI solutions that deliver measurable business value.
 * Lead architecture and design sessions and develop Data/AI and analytics roadmaps for PoCs and MVPs.
 * Support enterprise AI adoption and ensure long-term technical scalability and viability.
 * Stay current with emerging AI/GenAI capabilities, technologies, and market trends.
 * Mentor technical teams and contribute to technical communities and best practices.