Senior Platform AI Engineer
Tasks
- Build RAG systems with vector storage and indexing
- Create AI specific CI CD patterns for reproducible deployments
- Design AI workflow observability and cost tracking
- Design and build MCP servers for AI agents
- Develop AI optimized API schemas
- Develop caching layers and token aware request routing
- Implement document parsing pipelines and retrieval filtering
- Implement tool routing and execution runtimes
- Manage agent state and long running processes
- Monitor output quality and workflow performance
- Operate LLM model lifecycle and production pipelines
- Orchestrate multi-step agent workflows
- Perform prompt versioning and A B testing
- Plan token capacity and manage rate governance
- Support platform enablement for developer experience
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | API Design | AWS | Amazon Bedrock | Amazon SageMaker | Anthropic Claude | Anthropic Claude API | B testing | CI/CD | Claude API | Distributed Systems | Docker | ECS | Embeddings | Infrastructure as Code | Kubernetes | LLM APIs | Model Serving | Node.js | OpenAI API | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | S3 | Terraform | TypeScript | VLLM | Vector Databases | Workflow Orchestration | “as-code”
Education
N/A
Regions
Countries
States
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