Senior AI Engineer :: Remote :: Only W2 Position

Title: AI Engineer

Location: Remote 

Duration: 2 Year Contract

Required Skills & Experience

·       5+ years of full-time experience in electronic data processing systems study, design, and programming.

·       Bachelor’s degree in an IT-related or Engineering field; additional qualifying experience may be substituted on a year-for-year basis.

·       4+ years of experience designing, developing, and implementing applications in C# and containerized environments such as Docker and Kubernetes.

·       2+ years of experience working with AI/ML models, including fine-tuning and integrating models using AWS Bedrock and Azure AI services.

·       3+ years of experience working with RESTful APIs and integrating external services into enterprise applications.

·       3+ years of experience building CI/CD pipelines for AI models using GitHub Actions and Terraform.

Nice to Have Skills & Experience

·       3+ years of experience with AI frameworks such as LangChain, MLflow, Hugging Face, or TensorFlow, plus 2+ years of Infrastructure as Code experience with Terraform or AWS CloudFormation.

·       2+ years of experience developing AI-powered chatbots, decision-support systems, or automation agents, along with implementing security best practices for cloud-based AI services.

·       2+ years of experience optimizing AI models for performance and cost efficiency in AWS and Azure; prior experience supporting healthcare or government-related AI applications is preferred.

Job Description

Client is seeking a Senior AI Engineer to join a critical project with one of the largest consulting and advisory firms in the world.

This role will support a cloud-native AI engineering initiative for the State of California.

The Senior AI Engineer will help design, build, and deploy AI agents and workflow-driven applications that integrate with enterprise platforms and external services.

This person should bring strong hands-on experience across C#, containerized environments, AI/ML services, REST APIs, and modern CI/CD practices to deliver scalable, secure, and production-ready solutions.

·       Design, develop, and implement cloud-native applications in C# to support AI-driven workflows and agent-based solutions.

·       Build and deploy services within containerized environments such as Docker and Kubernetes.

·       Develop and integrate AI and ML capabilities using AWS Bedrock and Azure AI services, including model fine-tuning and enterprise integration.

·       Create and maintain RESTful APIs and connect external services into broader enterprise application architectures.

·       Support the development of AI model deployment pipelines using GitHub Actions and Terraform.

·       Partner with technical teams to deliver secure, scalable, and efficient AI solutions within AWS and Azure environments.

·       Contribute to the design of automation agents, decision-support capabilities, and chatbot-style experiences where applicable.

·       Apply engineering best practices to optimize application and model performance, reliability, and cost efficiency.

·       Help establish reusable development patterns and workflows for AI solutions operating within a cloud-native platform environment.