Fully Remote Senior Developer / AI Engineer

Position Title: Fully Remote Senior Developer / AI Engineer Location: Remote, United States Client: Long-Term Federal Government Program Employment Type: Full-Time | Contract Work Authorization: U.S. Citizenship Required Security Requirement: Must be eligible to obtain and maintain a favorable Federal Public Trust suitability determination. Anticipated Start: October 2026 Critical Evaluation Criteria: Individual must be a US Citizen and eligible for Security Clearance. All work can only be performed on Government issued laptop inside the US. Due to the sensitive nature of the work, we require the candidate to present his/her Driver's License and/or US Passport for verification during the Teams Video interview. How to Apply: Email your resume: careers@wintrio.com Job Summary WINTrio LLC is seeking an experienced Senior Developer / AI Engineer to design, develop, integrate, optimize, and operationalize Artificial Intelligence and Machine Learning solutions supporting mission-critical Federal Government programs. The successful candidate will work across the full lifecycle of enterprise AI solutions, including generative AI, retrieval-augmented generation (RAG), chatbots and virtual assistants, predictive analytics, document processing, anomaly and fraud detection, data science workloads, and AI-enabled automation. Key Responsibilities • Design, develop, evaluate, and optimize machine learning models, algorithms, and production-ready AI solutions. • Analyze large and complex datasets, perform feature engineering, and extract actionable insights to support model development. • Develop, tune, and improve AI/ML model performance, accuracy, scalability, and maintainability. • Collaborate with Data Scientists and Software Engineers to integrate AI/ML models into production systems. • Build and support AI solutions such as predictive models, RAG applications, chatbots, document processing, fraud detection, and optimization solutions. • Develop and maintain AI/ML engineering workflows using Python, R, or JavaScript, along with Terraform, CI/CD pipelines, and Git-based source control. • Integrate observability, monitoring, logging, and performance-management capabilities into AI/ML solutions. • Document AI/ML models, experiments, configurations, performance results, deployment processes, and engineering procedures. Required Qualifications • Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. • Five (5) to ten (10) years of relevant AI, Machine Learning, software engineering, or application development experience. • Hands-on experience designing and developing machine learning models and algorithms. • Strong understanding of machine learning principles and modern AI technologies. • Experience implementing, evaluating, tuning, and optimizing AI/ML solutions. • Experience integrating machine learning models into production systems. • Experience analyzing large and complex datasets. • Familiarity with deep learning frameworks. • Strong proficiency in Python, R, JavaScript, or related programming languages. • Experience with Terraform or comparable Infrastructure as Code technologies. • Expertise managing CI/CD pipelines. • Experience with Git-based code management and version control. • Experience integrating observability tools into AI/ML development and engineering. • Strong analytical, testing, debugging, documentation, and problem-solving skills. • U.S. Citizenship required. • Ability to obtain and maintain favorable Federal Public Trust suitability. Technical Areas AI / ML Generative AI Machine Learning Deep Learning Predictive Modeling Supervised Learning Unsupervised Learning Model Evaluation Model Tuning Anomaly Detection Fraud Detection Routing and Optimization Workload Forecasting Generative AI and RAG Retrieval-Augmented Generation Large Language Models Chatbots Virtual Assistants Prompt Engineering Semantic Search Document Summarization Document Translation Enterprise Search Data Science Data Preprocessing Feature Engineering Statistical Analysis Complex Dataset Analysis Model Performance Evaluation Data Quality Predictive Analytics Tools and Platforms Programming Python R JavaScript Full-stack web development technologies AI / ML Large Language Models Deep Learning Frameworks Azure OpenAI Azure Machine Learning AWS SageMaker Google Vertex AI Generative AI frameworks RAG architectures Infrastructure and DevOps Terraform Git CI/CD Pipelines Infrastructure as Code DevSecOps Automated Testing Deployment Automation Cloud Platforms Microsoft Azure Amazon Web Services Google Cloud Platform Software Engineering REST APIs Relational Databases Observability Tools Testing Frameworks Logging and Monitoring Application Performance Monitoring Sof