Service Architecture Manager
Core
Define strategy and architecture for an enterprise AI platform at global telecom scale, shaping secure, reliable cloud-native capabilities that automate and augment managed service operations across ML/LLM platforms, MLOps, vector databases, knowledge graphs, RAG, and Agentic AI.
Role type
Senior AI & Cloud Architect (Enterprise Architecture)
Builds
Enterprise AI platform, cloud-native capabilities, reference architectures for LLM/RAG/multi-agent solutions, multi-region ML inference, MLOps governance, agent orchestration, and graph-enhanced reasoning systems.
Domain
Telecom, Artificial Intelligence, Machine Learning, Cloud Computing, Enterprise Architecture
Deliverable
production ML models
Required skills
Enterprise architecture (TOGAF), Cloud-native design (AWS/Azure/GCP), MLOps governance, Vector database standards, Knowledge graph architecture, Agentic AI/LLM system design, Python, PySpark, Distributed ML, Security & compliance (GDPR/AI Act), Observability (OpenTelemetry/SRE), GPU FinOps
Preferred skills
Advanced degree in CS/AI/ML, Multi-cloud experience, Experience with open-source and licensed models, Experience with LangGraph/AutoGen/CrewAI/Semantic Kernel, Experience with Terraform/Pulumi/Kubeflow/MLflow
Technologies
AWS, Azure, GCP, vLLM, TGI, Triton, Pinecone, pgvector, Weaviate, Milvus, Neo4j, Neptune, Cypher, SPARQL, Python, PySpark, Spark, SQL, Kafka, Flink, Delta Lake, Iceberg, Terraform, Pulumi, Kubeflow, MLflow, W&B, LangGraph, AutoGen, CrewAI, Semantic Kernel, OpenTelemetry, Prometheus, Grafana
