Senior Manager, Automation Platform Engineering

EchoStar•Littleton, CO

5d•Onsite

About The Position

EchoStar is seeking a Senior Manager, Automation Platform Engineering to lead the design and development of a proprietary software ecosystem for AI-augmented autonomous operations. This role addresses current network operation inefficiencies by architecting self-healing systems to reduce Mean Time To Repair (MTTR) and optimize Operational Expenditures (OpEx). The goal is to transition the organization towards AI-augmented autonomous operations by bridging the gap between technical debt and business outcomes.

Requirements

Master-level proficiency in modern programming languages and software architecture for distributed systems.
Critical experience managing 5G/Open RAN infrastructures within cloud-native Kubernetes environments.
Advanced understanding of AI Architecture, specifically distinguishing between Traditional ML for anomaly detection and Generative AI for remediation.
Proven ability to create a technical vision from scratch, evidenced by a history of industry-leading blueprints or complex systems design.
Expertise in articulating the business value of technical debt reduction and quantifying the ROI of automation initiatives.
Strategic AI Literacy and the ability to innovate workflows by applying autonomous logic to replace manual intervention.
Minimum Education: Bachelor’s Degree in Computer Science, Engineering, or a related technical field.
Minimum Experience: 8+ years of experience in Software Engineering or Network Automation.
Required Technical Skills: Must have at least 5 years of experience with: Modern programming languages (Python, Go, or similar), Cloud-native orchestration and Kubernetes-based workloads, 5G or Open RAN infrastructure integration.

Responsibilities

Lead the end-to-end design and development of scalable, proprietary automation software used to diagnose and resolve production issues at a nationwide scale.
Drive the platform roadmap toward Closed-Loop AI Automation, prioritizing the evolution from basic scripts to intelligent, self-healing recovery workflows.
Architect high-concurrency, event-driven systems using Kafka and Microservices to replace legacy manual processes with robust internal tools.
Oversee the integration of Traditional and Generative AI models within distributed Kubernetes-based workloads to ensure reliable, proactive network mitigation.
Translate technical milestones, such as Zero Touch Provisioning (ZTP), into clear financial impacts and accelerated time-to-market outcomes.
Foster an environment of expert-level development, ensuring internal engineering initiatives meet the same rigor and security standards as customer-facing products.