AI/ML Lead/Architect

Position: AI/ML Lead/Architect

Location: Hybrid from Reston, VA or Houston, TX.

We are seeking a highly skilled AI/ML resource to design, develop, and deploy modern applications enhanced with advanced Artificial Intelligence capabilities on Microsoft Azure.

This role focuses on AI/ML development, Generative AI, Retrieval Augmented Generation (RAG) pipelines, ML model development, MLOps, and enterprise-scale cloud deployment.

You will collaborate with architects, software engineers, data engineers, and business stakeholders to translate requirements into production-grade AI-powered software solutions.

The ideal candidate brings strong software engineering fundamentals combined with hands-on experience developing and operationalizing AI/ML systems on Microsoft Azure.

Education and Experience Requirements Requires :

in AI/ML development, including designing and deploying ML models.

Strong software engineering background: Python, REST APIs, microservices, event-driven systems.

Good knowledge and understanding of RESTful API principles.

Good understanding of relational databases and querying using SQL.

Required Technical Experience Hands-on experience with Azure Machine Learning, Azure OpenAI, Cognitive Services, and Azure Data Lake.

Experience building RAG systems, vector embeddings, and knowledge retrieval.

Perform data preprocessing, feature engineering, model training, hyperparameter tuning, validation, and performance optimization.

Ensure resilience, scalability, and reliability of AI models using cloud-based platforms such as Azure AI/ML.

Ensure AI/ML solutions align with enterprise security, compliance, and governance requirements.

Develop prompts, system instructions, and orchestration patterns to ensure quality, reliability, and cost efficiency.

AI Agents and Agentic Automation Design and implement single-agent and multi-agent workflows for complex enterprise processes using Azure and modern orchestration frameworks.

Application and Platform Development Implement secure, scalable integrations with cloud data and AI services.

Participate in code reviews, architecture discussions, and Agile ceremonies. Utilize Git and GitHub for version control and DevOps workflows.

Apply software design patterns and best practices in application development.