Node.Digital

Automation / AIOps Engineer

Posted 2 Days Ago

Be an Early Applicant

Washington, DC, USA

In-Office

Mid level

Artificial Intelligence • Software

The Role

Designs, implements, and maintains automation workflows and IaC/RPA solutions; applies AIOps and ML-driven analytics to detect, correlate, and resolve infrastructure issues; optimizes capacity, performance, patching, backups, and reporting; collaborates with cross-functional teams.

Summary Generated by Built In

Automation / AIOps Engineer

Location: Washington, DC

Preferred: US Citizen

Job Description:

The Automation / AIOps Engineer will be responsible for developing, implementing, and maintaining automation workflows, scripts, orchestration routines, and reusable templates to support provisioning, configuration, maintenance, monitoring response, patching, backup validation, reporting, and other operational activities within FA1. This individual will leverage Infrastructure as Code (IaC), Robotic Process Automation (RPA), and AIOps capabilities to transform repetitive, manual tasks into automated, repeatable, and measurable outcomes. The role includes applying advanced analytics and machine learning-driven insights to proactively identify, correlate, and resolve infrastructure and platform issues, optimize capacity and performance, and reduce mean time to detect (MTTD) and mean time to restore (MTTR).

Requirements

Required Skills:

Strong expertise in automation technologies, including Infrastructure as Code (IaC), Robotic Process Automation (RPA), and orchestration tools.
Proficiency in AIOps practices, including the use of artificial intelligence and machine learning for operational decision support.
Experience in developing and maintaining automation workflows, scripts, and templates.
Ability to apply advanced analytics and machine learning models to improve operational outcomes.
Technical knowledge of cloud-native environments, virtualization platforms, and enterprise storage systems.
Strong problem-solving skills to detect operational drift and emerging failure conditions.
Excellent communication and collaboration abilities to work with cross-functional teams and stakeholders.

Nice To Have:

Familiarity with natural language processing (NLP), computer vision, and TensorFlow-based ML models.
Experience with scikit-learn and pandas for processing operational data at scale.
Knowledge of AI/ML pipelines and foundation model prompts.
Understanding of FinOps practices and cost management tools.
Experience with ServiceNow, monitoring tools, and configuration repositories.
Ability to collaborate with infrastructure automation teams and other contractor teams.

Certifications:

Relevant certifications in automation technologies, such as Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), or similar.
Certifications in AIOps and machine learning, such as AWS Certified Machine Learning – Specialty or Google Cloud Professional Machine Learning Engineer.

Benefits

We are proud to offer competitive compensation and benefits packages to include

Medical
Dental
Vision
Basic Life
Health Saving Account
401K matching
Three weeks of PTO/Sick
11 Paid Holidays
Pre-Approved Online Training

Skills Required

Expertise in automation technologies including Infrastructure as Code (IaC), Robotic Process Automation (RPA), and orchestration tools
Proficiency in AIOps practices using AI and machine learning for operational decision support
Experience developing and maintaining automation workflows, scripts, and reusable templates
Ability to apply advanced analytics and machine learning models to improve operational outcomes
Technical knowledge of cloud-native environments, virtualization platforms, and enterprise storage systems
Strong problem-solving skills to detect operational drift and emerging failure conditions
Excellent communication and collaboration abilities to work with cross-functional teams and stakeholders
Familiarity with natural language processing (NLP), computer vision, and TensorFlow-based ML models
Experience with scikit-learn and pandas for processing operational data at scale
Knowledge of AI/ML pipelines and foundation model prompts
Understanding of FinOps practices and cost management tools
Experience with ServiceNow, monitoring tools, and configuration repositories
Ability to collaborate with infrastructure automation teams and other contractor teams
Relevant certifications such as Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), AWS Certified Machine Learning - Specialty, or Google Cloud Professional Machine Learning Engineer