Senior Applied AI Engineer
USD 160K-210K (estimate) Senior-level Full Time
Tasks
- Architect and build stateful graph based agent workflows with tool use planning and memory
- Build high reliability APIs and streaming services for real time inference speech and vision
- Implement production readiness tracing logging metrics rate limiting circuit breakers and SLOs
- Implement retrieval and memory hybrid search vector and graph retrieval semantic caches and long horizon context
- Integrate LLMs and multimodal models via structured input output and function calling
- Mentor engineers through design docs and architecture decisions
- Optimize cost and latency model routing prompt and tool selection quantization and KV cache and prefill strategies
- Partner with teams to translate research into production systems and iterate through evaluation gates
- Stand up eval pipelines offline golden sets LLM as judge human rubrics online A B and CI regression tests
Perks/Benefits
Skills/Tech-stack
API Design | AWS | CI/CD | Circuit Breakers | Docker | Event Driven | Event-driven architecture | FastAPI | Flask | Function Calling | GCP | GPU autoscaling | GitHub Actions | Go | Graph RAG | Human-in-the-loop | Hybrid search | JSON Schema | Kubernetes | LLM | LLM-as-judge | Logging | Metrics | Milvus | Multimodal Models | Observability | OpenTelemetry | PGVector | Pinecone | PostgreSQL | Pydantic | Python | Rate Limiting | Regression testing | Retrieval-Augmented Generation | SLOs | Streaming APIs | Structured data | Terraform | The Loop | Tool-Calling | Tracing | Vector Databases | Weaviate
Education
N/A
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