AI Sustaining Engineer

Overview

Remote
$65 - $70
Contract - W2
Contract - 6 Month(s)

Skills

Monitor performance
AI monitoring
Dynatrace

Job Details

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

  1. Production Support Experience
    • Ability to troubleshoot and resolve issues in live AI systems.
    • Familiarity with incident management and root cause analysis.
  2. Monitoring Tools Expertise
    • Hands-on experience with Dynatrace and Optura EMA for performance and usage monitoring.
    • Understanding of system drift and anomaly detection.
  3. Metrics & Reporting
    • Strong skills in tracking KPIs, ROI, and performance metrics.
    • Ability to generate actionable insights from monitoring data.

Operational Needs

  1. AI System Performance Monitoring
    • Regular tracking of model accuracy, latency, and resource usage.
    • Identifying degradation or drift in AI models over time.
  2. Post-Implementation Analysis
    • Measuring business impact and ROI of deployed AI solutions.
    • Communicating findings to stakeholders effectively.

Compliance & Governance Needs

  1. AI Governance Knowledge
    • Familiarity with AI policy frameworks and ethical guidelines.
    • Experience reporting violations and ensuring regulatory compliance.
  2. Risk Management
    • Understanding of data privacy, bias detection, and model explainability.
    • Ability to escalate and mitigate risks in AI deployments.
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