Specialty Software Engineer

Senior Full Stack AI/ML Engineer

Location: Charlotte, NC (Preferred), Irving, TX, Minneapolis, MN, or Chandler, AZ
Work Model: Hybrid (3 days onsite, 2 days remote)
Employment Type: Contract with potential for full-time conversion
Authorization: Candidates must be authorized to work in the . without current or future sponsorship requirements.

About the Role

We are seeking a highly skilled Senior Full Stack AI/ML Engineer to design, develop, and deploy scalable AI-powered applications and cloud-native solutions. In this role, you will work across the full technology stack, leveraging modern cloud platforms, machine learning technologies, and software engineering best practices to deliver innovative products and business solutions.

You will collaborate with cross-functional teams including product managers, architects, data scientists, engineers, and business stakeholders to build intelligent applications that drive business value.

Responsibilities

• Design, develop, and deploy full-stack applications using Python for backend services and React for modern user interfaces.
• Build and integrate AI/ML solutions, including large language model (LLM) applications, generative AI capabilities, and conversational AI experiences.
• Develop scalable APIs, microservices, and distributed systems supporting enterprise-grade applications.
• Architect and implement cloud-native solutions across Microsoft Azure, with exposure to AWS and Google Cloud Platform (GCP).
• Design and implement Retrieval-Augmented Generation (RAG) architectures, prompt orchestration workflows, and AI-powered knowledge solutions.
• Collaborate with data scientists and engineering teams to operationalize machine learning models from development through production.
• Establish and maintain MLOps processes, including model deployment, monitoring, evaluation, lifecycle management, and optimization.
• Implement CI/CD pipelines, automated deployments, infrastructure-as-code, and DevOps best practices.
• Design secure, scalable, and reliable application architectures that meet enterprise standards.
• Work in Agile environments using Scrum, SAFe, or Kanban methodologies.

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• Strong hands-on experience in full-stack software engineering.
• Proficiency in Python and modern frontend frameworks such as React.
• Experience developing and consuming REST APIs, microservices, and distributed applications.
• Experience building, deploying, and supporting cloud-native applications on Microsoft Azure.
• Experience developing machine learning and AI solutions using structured and unstructured datasets.
• Experience implementing DevOps practices, including CI/CD, automated deployments, monitoring, and environment management.
• Experience with relational and NoSQL databases.
• Excellent communication, collaboration, and problem-solving skills.

Preferred Qualifications

• Experience with cloud services such as:Azure Machine LearningAzure FunctionsAzure App ServicesAzure DevOpsAWS LambdaAmazon SageMakerGoogle Vertex AIGoogle Cloud Run
• Experience with:Large Language Models (LLMs)Generative AINatural Language Processing (NLP)Retrieval-Augmented Generation (RAG)Prompt engineering and orchestration frameworks
• Experience designing multi-cloud architectures and integration patterns across Azure, AWS, and GCP.
• Experience with containerization and orchestration technologies, including Docker and Kubernetes.
• Experience building chatbot and conversational AI solutions.
• Knowledge of MLOps frameworks, model governance, and production monitoring.
• Experience with vector databases and semantic search technologies.
• Strong understanding of cloud architecture, security, scalability, and reliability principles.
• Experience with Agile delivery methodologies and Azure DevOps.

Preferred Technical Skills

• Python
• React
• Azure Cloud Services
• Azure DevOps
• CI/CD Pipelines
• AI/ML Engineering
• AI Solution Development
• AI Model Development
• Large Language Models (LLMs)
• Generative AI
• Data Analytics
• Relational, NoSQL, and Vector Databases
• REST APIs and Microservices
• Docker and Kubernetes
• AWS and Google Cloud Platform
• Agile (Scrum, SAFe, Kanban)

What You'll Bring

• A passion for building innovative AI-powered solutions at scale.
• A strong engineering mindset focused on quality, reliability, and continuous improvement.
• The ability to influence technical direction and collaborate effectively across teams.
• A customer-focused approach to solving complex business and technology challenges.

This version mirrors the concise, impact-oriented style commonly seen in Google and other leading technology company job postings.