Certificates, Licenses, Registrations
Specific Certifications are not required. There are a few that can demonstrate significant understanding of key concepts.
· Microsoft Certified: Azure AI Engineer Associate
· Microsoft Certified: Azure Solutions Architect Expert
· Microsoft Certified: DevOps Engineer Expert
· AWS Certified Machine Learning Engineer - Associate or AWS Certified Machine Learning - Specialty
· Google Cloud Professional Machine Learning Engineer
· Databricks Certified Machine Learning Professional
· Certified Kubernetes Application Developer or Certified Kubernetes Administrator
· Relevant responsible AI, cloud security, data engineering, or architecture certifications
· Demonstrated ability to distinguish deterministic automation responsibilities from agentic orchestration and AI-consumption responsibilities.
· Experience establishing reusable agent architectures, development standards, governance patterns, and evaluation methods.
· Experience with MCP, Semantic Kernel, LangGraph, LangChain, Azure AI services, Azure OpenAI, or comparable agent and orchestration frameworks.
· Experience with retrieval-augmented generation, embeddings, vector search, graph-based retrieval, and knowledge packaging.
· Understanding of AI safety, hallucination reduction, prompt injection risks, tool-use controls, auditability, and human approval patterns.
· Ability to evaluate AI-generated outputs and agent actions for correctness, safety, reliability, and operational impact.
· Ability to translate engineering procedures, operational knowledge, and business processes into governed agentic workflows.
· Ability to communicate complex architecture, risks, tradeoffs, and technical recommendations to technical and non-technical stakeholders.
· Strong technical leadership, mentoring, problem-solving, and cross-functional collaboration skills.
· Ability to work effectively with Network Automation Engineers, Platform Engineers, Data Engineers, NMS Engineers, Reporting Engineers, Capacity Engineers, Network Security, and Infrastructure Engineering.
· Adaptability and willingness to evaluate emerging AI technologies while maintaining disciplined production standards.
· Ownership mindset and accountability for architecture quality, production readiness, governance, and delivery outcomes.
· Position may require occasional on-call availability.
· Position may require up to 10% travel.