Full Stack AIML Engineer (.NET)

Full Stack AI/ML Engineer (.NET)

Location: Fort Mill NC (Primary) New York NY

Employment Type: Full-Time Permanent Experience: 8 12 Years

Role Summary

We are looking for a skilled Full Stack AI/ML Engineer with development experience to design build and deploy intelligent applications that combine robust backend engineering with applied machine learning capabilities. The ideal candidate bridges the gap between traditional enterprise software development and modern AI/ML systems delivering end-to-end solutions from data pipelines to production-ready user interfaces.

Key Responsibilities

Full Stack Development

• Design and develop scalable high-performance applications (C#) Core and REST/GraphQL APIs.
• Build responsive intuitive frontend interfaces using React Angular or Blazor.
• Architect microservices and event-driven systems using Amazon SQS SNS Kafka or RabbitMQ.
• Integrate with relational (SQL Server PostgreSQL Amazon RDS) and NoSQL (MongoDB DynamoDB) databases.
• Ensure application security performance and code quality through design reviews unit testing and CI/CD best practices.

AI / ML Engineering

• Design develop and deploy machine learning models for use cases such as classification regression anomaly detection recommendation and NLP.
• Integrate large language models (LLMs) - including Amazon Bedrock OpenAI or open-source alternatives - into enterprise applications via APIs and prompt engineering.
• Build and maintain ML pipelines using Amazon SageMaker MLflow or AWS Step Functions.
• Implement RAG (Retrieval-Augmented Generation) architectures vector databases (Pinecone Weaviate Amazon OpenSearch) and embedding models.
• Monitor model performance in production manage model drift and implement retraining workflows.
• Collaborate with data engineers to ensure high-quality feature engineering and data availability.

Cloud & DevOps

• Deploy and manage applications on Amazon Web Services (AWS) - including EC2 ECS/EKS Lambda S3 and API Gateway.
• Build and maintain CI/CD pipelines using AWS CodePipeline GitHub Actions or Jenkins.
• Implement infrastructure-as-code using Terraform or AWS CloudFormation / CDK.
• Ensure observability through logging monitoring and alerting using Amazon CloudWatch Datadog or Grafana.

Collaboration & Leadership

• Work closely with product managers data scientists and UX designers to translate business requirements into technical solutions.
• Mentor junior engineers and conduct code and architecture reviews.
• Participate in Agile ceremonies (sprint planning retrospectives stand-ups).
• Document technical designs APIs and AI model specifications clearly.

Required Qualifications

• 8 years of software engineering experience with at least 4 years focused (C# / Core).
• Hands-on experience building and deploying ML models using Python-based frameworks such as Scikit-learn PyTorch or TensorFlow.
• Practical experience integrating LLMs and generative AI capabilities into production applications.
• Strong proficiency with frontend frameworks - React Angular or Blazor.
• Solid understanding of RESTful API design microservices architecture and event-driven systems.
• Strong experience with AWS cloud services (SageMaker Bedrock Lambda ECS/EKS S3 RDS DynamoDB).
• Proficiency with SQL and experience with NoSQL data stores.
• Hands-on experience with Git CI/CD pipelines and Agile development methodologies.
• Strong problem-solving skills and ability to work independently in a fast-paced environment.

Preferred Qualifications

• Experience with MLOps frameworks (MLflow SageMaker Pipelines SageMaker Model Registry).
• Familiarity with vector databases and RAG-based architectures.
• Exposure to prompt engineering fine-tuning or LLM orchestration frameworks (LangChain Semantic Kernel AWS Bedrock Agents).
• Knowledge of financial services or banking domain.
• AWS certifications (Solutions Architect ML Specialty or Developer Associate) are a plus.
• Experience with containerization (Docker Kubernetes / Amazon EKS).