AI Engineer (Machine Learning/Cloud Infrastructure)

ResponsibilitiesAI Infrastructure & Environment ManagementManage and maintain cloud environments for AI workloads Ensure secure and stable connectivity between enterprise systems and AI platformsMonitor system performance and maintain reliability of AI models in productionImplement security controls for AI data handling and model deploymentAI Prototyping & Technical EvaluationConduct technical evaluation of AI tools, frameworks, and vendor solutionsBuild proof-of-concepts to validate AI feasibility and performanceStress-test AI APIs, model endpoints, and third-party integrationsDocument findings and provide recommendations on AI adoptionData Pipelines & MLOps EngineeringDevelop and maintain data pipelines for AI training and inferenceImplement MLOps practices for model deployment, monitoring, and lifecycle managementBuild and maintain model serving infrastructure and APIsEnsure reliable data flow between source systems and AI modelRequirementsDegree in Computer Science, Data Science, AI/ML, or related field3+ years of experience in AI/ML engineering or related technical rolesStrong Python programming skills with ML libraries (TensorFlow, PyTorch, scikit-learn)Experience with cloud platforms (AWS, Azure, or GCP)Knowledge of MLOps, model deployment, and monitoringExperience with API development and integration for AI servicesUnderstanding of data pipelines and ETL processesFamiliarity with government technology standards and AI governance frameworksExperience with Government Commercial Cloud (GCC) or similar secure environments