Artificial Intelligence Integration Engineer

We are seeking a skilled Artificial Intelligence Integration Engineerto join our team and ensure the seamless deployment monitoring and optimization of AI models in production.

The AI Intelligence Engineerwill design implement and maintain end-to-end machine learning pipelines focusing on automating model deployment monitoring model health detecting data drift and managing AI-related logging. This role will involve building scalable infrastructure and dashboards for real-time and historical insights ensuring models are secure performant and aligned with business needs.

Key Responsibilities

• Model Deployment: Deploy and manage machine learning models in production using tools like MLflow Kubeflow or AWS SageMaker ensuring scalability and low latency.

• Monitoring and Observability: Build and maintain dashboards using Grafana Prometheus or Kibana to track real-time model health (e.g. accuracy latency) and historical trends.

• Data Drift Detection: Implement drift detection pipelines using tools like Evidently AI or Alibi Detect to identify shifts in data distributions and trigger alerts or retraining.

• Logging and Tracing: Set up centralized logging with ELK Stack or OpenTelemetry to capture AI inference events errors and audit trails for debugging and compliance.

• Pipeline Automation: Develop CI/CD pipelines with GitHub Actions or Jenkins to automate model updates testing and deployment.

• Security and Compliance: Apply secure-by-design principles to protect data pipelines and models using encryption access controls and compliance with regulations like GDPR or NIST AI RMF.

• Collaboration: Work with data scientists AI Integration Engineers and DevOps teams to align model performance with business requirements and infrastructure capabilities.

• Optimization: Optimize models for production (e.g. via quantization or pruning) and ensure efficient resource usage on cloud platforms like AWS Azure or Google Cloud.

• Documentation: Maintain clear documentation of pipelines dashboards and monitoring processes for cross-team transparency.

• • • Education: Bachelors or Masters degree in Computer Science Data Science Engineering or a related field.
    • Experience:
    • 5 years in MLOps DevOps or software engineering with a focus on AI/ML systems.
    • Proven experience deploying models in production using MLflow Kubeflow or cloud platforms (AWS SageMaker Azure ML).
    • Hands-on experience with observability tools like Prometheus Grafana or Datadog for real-time monitoring.
    • Technical Skills:
    • Proficiency in Python and SQL; familiarity with JavaScript or Go is a plus.
    • Expertise in containerization (Docker Kubernetes) and CI/CD tools (GitHub Actions Jenkins).
    • Knowledge of time-series databases (e.g. InfluxDB TimescaleDB) and logging frameworks (e.g. ELK Stack OpenTelemetry).
    • Experience with drift detection tools (e.g. Evidently AI Alibi Detect) and visualization libraries (e.g. Plotly Seaborn).
    • AI-Specific Skills:
    • Understanding of model performance metrics (e.g. precision recall AUC) and drift detection methods (e.g. KS test PSI).
    • Familiarity with AI vulnerabilities (e.g. data poisoning adversarial attacks) and mitigation tools like Adversarial Robustness Toolbox (ART).
    • Soft Skills:
    • Strong problem-solving and debugging skills for resolving pipeline and monitoring issues.
    • Excellent collaboration and communication skills to work with cross-functional teams.
    • Attention to detail for ensuring accurate and secure dashboard reporting.
  • *Must be eligible to obtain a Department of Homeland Security EOD clearance ( Requirements 1. US Citizenship 2. Favorable Background Investigation)

• • • Experience with LLM monitoring tools like LangSmith or Helicone for generative AI applications.
    • Knowledge of compliance frameworks (e.g. GDPR HIPAA) for secure data handling.
    • Contributions to open-source MLOps projects or familiarity with X platform discussions on #MLOps or #AIOps.

Formed through the strategic union of Sev1Tech and ERT Entarian is a premier provider of mission-critical engineering and technology solutions. Founded on a legacy of excellence dating back to 1993 Entarian is a product of an evolved and fully diversified engineering and federal technology leader. From deep space to defense and civilian missions Entarian delivers secure mission-aligned digital solutions that drive national resilience and operational effectiveness. We dont just support modernization; we define it.

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Entarian is anEqual Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex pregnancy sexual orientation gender identity national origin age protected veteran status or disability status.