AI Sustaining Engineer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, PY DATA, INC., is seeking the following. Apply via Dice today! AI Sustaining Engineer Long term - Contract to hire (CTH) 100% Remote 4 positions Project Summary Client is building out an all-new AI team to support a multitude of initiatives. They are building out a vast roadmap through 2029 outlook, including use cases involving Prior Authorization, Rebates, Summarization. The AI Sustainability Engineer ensures that AI models deployed in production remain accurate, efficient, ethical, and cost-effective over time. This role bridges MLOps, observability, and optimization, focusing on performance monitoring, drift detection, retraining workflows, and sustainable resource use. Key Responsibilities: • Monitor AI model performance, reliability, and fairness in production. • Detect and remediate data drift, bias, and degradation issues. • Optimize model inference efficiency, scalability, and energy usage. • Implement observability frameworks and automated retraining triggers. • Collaborate with AI Engineers and infrastructure teams to sustain production health. • Provide technical support and troubleshooting for live AI systems. • Report AI policy violations and ensure compliance. Must Have Skills • Experience with ML observability tools (Dynatrace, MLflow, EvidentlyAI, Prometheus, Grafana, etc.). • Strong understanding of data drift detection and statistical monitoring. • Hands-on with containerization (Docker/Kubernetes) and CI/CD pipelines. • Experience in production support and AI monitoring. • Proficient in Python for automation and monitoring scripts. • Familiarity with model versioning, governance, and retraining pipelines. • Knowledge of AWS cloud AI infrastructure (containerized deployments on EC2 instances). • Strong communication, team player, go-getter type attitude. Must be proactive and seeking out work and solutions, good working in ambiguity and not always being handed instructions. Responsibilities: • Provide technical support and troubleshooting for live AI systems. • Monitor performance, usage, and drift. • Report AI policy violations and ensure compliance. • Measure ROI and performance post-implementation Qualifications: • Experience in production support and AI monitoring. • Familiarity with Dynatrace, Optura EMA, and AI governance. • Strong metrics and reporting capabilities. Top Technical Needs • Production Support Experience • Ability to troubleshoot and resolve issues in live AI systems. • Familiarity with incident management and root cause analysis. • Monitoring Tools Expertise • Hands-on experience with Dynatrace and Optura EMA for performance and usage monitoring. • Understanding of system drift and anomaly detection. • Metrics & Reporting • Strong skills in tracking KPIs, ROI, and performance metrics. • Ability to generate actionable insights from monitoring data. Operational Needs • AI System Performance Monitoring • Regular tracking of model accuracy, latency, and resource usage. • Identifying degradation or drift in AI models over time. • Post-Implementation Analysis • Measuring business impact and ROI of deployed AI solutions. • Communicating findings to stakeholders effectively. Compliance & Governance Needs • AI Governance Knowledge • Familiarity with AI policy frameworks and ethical guidelines. • Experience reporting violations and ensuring regulatory compliance. • Risk Management • Understanding of data privacy, bias detection, and model explainability. • Ability to escalate and mitigate risks in AI deployments.