AI Platform Engineer
Purpose
Build and
operate a shared AI platform enabling multiple telecom squads to develop and
deploy AI use cases efficiently.
Key Responsibilities
· Develop
AI platform services: model serving, vector DBs, feature stores, prompt
orchestration
· Enable
self-service capabilities for product squads (APIs, SDKs, pipelines)
· Integrate
with data platforms (Kafka, streaming, data lakes)
· Manage
GPU workloads, inference endpoints, scaling policies
· Ensure
platform supports low-latency use cases (e.g., real-time fraud detection)
Requirements
· Strong
backend/platform engineering (Python, Go, Java)
· Experience
with ML platforms (SageMaker, Vertex AI, Databricks)
· Vector
DBs (Pine-cone, Weaviate, FAISS), API gateways
· Kubernetes,
container orchestration
Benefits
· Platform
uptime
· Developer
adoption rate
· Cost
per inference / request