Senior Platform Engineer – Data & AI
Tasks
- Architect and build cloud native platforms on Google Cloud
- Build RAG pipelines and vector search
- Build multi-agent orchestration systems
- Build real-time and batch data pipelines
- Design agent observability frameworks
- Design event-driven architectures
- Develop platform SDKs and reusable blueprints
- Develop scalable microservices and APIs
- Enable AI driven platform automation
- Enable CI CD and GitOps automation
- Enable self healing event driven automation
- Enforce data quality and lineage governance
- Implement agent communication protocols
- Implement data modeling semantic layer design
- Implement infrastructure-as-code with Terraform and Kubernetes
- Integrate LLMs and GenAI services
- Integrate OpenTelemetry Prometheus and Grafana
- Integrate agent gateway and routing
- Manage data cataloging and metadata
- Orchestrate agent lifecycle and task execution
- Support SRE and incident response improvements
Perks/Benefits
- N/A
Skills/Tech-stack
Agent systems | Airflow | Angular | Apache Kafka | Autogen | CI/CD | Cloud platform | Collibra | CrewAI | Data Catalog | Data Lineage | Data Modeling | Data Quality | Data fabric | Data mesh | Dataflow | Dataform | Datahub | Embeddings | Event Driven | Event-driven architecture | Faiss | Full Stack | GCP | GenAI | GitOps | Google Cloud | Google Cloud Platform | Google Pub/Sub | Grafana | GraphQL | Infrastructure as Code | Java | Kubernetes | LLM | Langgraph | Metadata Management | Microservices | Multi-Agent | Multi-Agent Systems | OpenAI | OpenTelemetry | Pinecone | Prometheus | Pub/Sub | Python | RAG | REST | React | SQL | Semantic layer | Spark | Spring Boot | Terraform | Vector Databases | Vertex AI | Vue.js | Weaviate | WebSockets | “as-code”
Education
N/A
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