Job Duties and ResponsibilitiesCandidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.EchoStar requires an enterprise architecture vision to enable AI-driven digital transformation across network, OSS/BSS, and cloud-native environments. This role bridges business strategy and technology execution by designing target-state frameworks, rationalizing technology stacks, and establishing governance standards. Solving key operational challenges involves embedding scalable machine learning solutions, real-time analytics, and automated decision-making into complex telecommunications infrastructure.
What Success Looks Like (Objectives)- Lead the enterprise AI architecture strategy to align digital transformation goals with measurable business outcomes across telecom systems
- Architect, train, and deploy production machine learning models for network optimization, predictive maintenance, and operational analytics
- Integrate AI/ML capability models into legacy and modern OSS/BSS platforms to automate high-volume decision-making
- Build resilient real-time streaming frameworks using cloud-native and edge computing principles for high-throughput network insights
- Establish robust governance, model lifecycle management, and ethical compliance standards to scale AI operations safely
- Guide cross-functional teams and junior engineers to accelerate experimentation and maintain technical alignment
Skills, Experience and RequirementsCore Skills and Competencies (What you'll bring)- Deep technical expertise in enterprise AI architecture, including proficiency with platforms such as AWS Bedrock, Google Vertex, Databricks, or IBM Watson and core ML frameworks
- Critical experience architecting and delivering large-scale AI solutions within telecommunications, mobile network, or cloud-native environments
- Advanced AI Application and Innovation capability to translate business requirements into scalable technology blueprints and automated systems
- Strong proficiency in real-time data streaming architectures, big data infrastructure (Kafka, Spark, Hadoop), and OSS/BSS system integration
- Demonstrated governance expertise in model lifecycle management, version control, explainability, and AI privacy frameworks
- Proven leadership skills in executive stakeholder management, cross-functional collaboration, and technical mentorship
Additional QualificationsSuccessful candidates will typically have:
- Hands-on experience with AI-powered network tuning, network slicing, and intent-based networking
- Familiarity with advanced AI techniques, including deep reinforcement learning, federated learning, and model explainability
- Knowledge of AI ethics, regulatory compliance in telecom, and data privacy frameworks
- TM Forum certifications
Minimum Requirements- Minimum Education: Bachelor's Degree in Computer Science, Engineering, Business, or a related technical discipline (Master's preferred)
- Minimum Experience: 12+ years of enterprise architecture experience, with demonstrated experience in telecommunications or mobile network operators
- Required Technical Skills:
- TOGAF certification (Level 1 and Level 2)
- AI/ML platforms and frameworks (TensorFlow, PyTorch, Scikit-learn, AWS Bedrock, Google Vertex, Databricks, IBM Watson)
- Big data processing tools (Kafka, Spark, Hadoop) and OSS/BSS systems
Salary RangesCompensation: $146,108.00/Year - $210,000.00/Year
BenefitsWe offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan; all benefits can be viewed here: EchoStar Benefits.
The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role's location and is subject to change based on work location.
The posting will be active for a minimum of 3 days. The active posting will continue to extend by 3 days until the position is filled.
