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# AI Architect (GenAI / MLOps)

- **Company:** SRI Tech Solutions Inc.
- **Location:** Charlotte, NC, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Data Architecture, Information Engineering, Python (Programming Language), Machine Learning, OpenAI, Tensorflow, Software Deployment, Data Streaming, AI Infrastructure, Pinecone, Feature Store, Google Cloud, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, IT Architecture, Model Validation, Llamaindex, Generative AI, Agentic-AI, Togaf, Pgvector, Data Lakes, AI Platforms, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, Drift Detection, Azure AI, Data Pipelines, OpenSearch, Docker, Microservices
- **Published:** October 21, 2026
- **Apply:** https://www.dice.com/job-detail/cbcdb083-acfe-4ff1-b16a-d861e0af3053

## About the Role

* 10+ years in software/data engineering, including 4+ years architecting production AI/ML solutions.
 * Hands-on expertise in LLMs, GenAI, prompt engineering, RAG, embeddings, and agent frameworks (LangChain/LlamaIndex).
 * Strong Python skills and experience with PyTorch, TensorFlow, or scikit-learn.
 * Experience with AWS, Azure, or Google Cloud Platform AI services (SageMaker, Bedrock, Azure OpenAI, or Vertex AI).
 * MLOps experience with MLflow, Kubeflow, Docker, Kubernetes, and CI/CD.
 * Strong understanding of data architecture, data lakes/warehouses, streaming, APIs, and microservices.
 * Knowledge of AI security, privacy, governance, and regulatory compliance.
 * Excellent communication and stakeholder management skills., * Banking, insurance, or wealth management experience; familiarity with SR 11-7 model risk guidelines.
 * Experience with Pinecone, pgvector, OpenSearch, fine-tuning, and model evaluation.
 * Cloud/architecture certifications such as AWS ML Specialty, Azure AI Engineer, or TOGAF.
 * Master's or PhD in Computer Science, Data Science, or a related field.

## Description

Design and lead enterprise AI/ML and Generative AI solutions from architecture through production deployment, ensuring scalability, security, compliance, and governance. Advise business leaders and mentor engineering teams on AI strategy and implementation., * Design end-to-end AI/GenAI architectures, including RAG, AI agents, fine-tuning, and model serving.

 * Evaluate LLMs, vector databases, orchestration frameworks, and MLOps tools.
 * Define reusable AI architecture standards and reference designs.
 * Collaborate on data pipelines, feature stores, and data quality.
 * Implement responsible AI, model governance, security, explainability, and compliance.
 * Establish MLOps/LLMOps practices for CI/CD, monitoring, model evaluation, drift detection, and cost optimization.
 * Lead AI proofs of concept and production deployments.
 * Advise executives on AI strategy, feasibility, and technical trade-offs.
 * Mentor engineers and data scientists and lead architecture reviews.