AI Engineering Manager
Tasks
- Develop team culture and provide coaching
- Directly manage engineers when needed
- Drive observability standards and alert thresholds
- Drive reliability and scalability of real time model serving
- Ensure compliance and confidentiality
- Lead drift detection and confidence scoring monitoring
- Lead engineering delivery of agentic interface
- Lead hiring and onboarding of engineers
- Lead machine learning pipeline engineering for usage insights
- Manage feature and data dependencies with cross functional teams
- Manage sprint cadence delivery
- Own LLM orchestration architecture
- Own customer insight modeling pipeline
- Own end to end engineering delivery of real time data serving infrastructure
- Prepare team health updates and milestone reviews
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AI Agents | API Gateway | Alert Threshold Management | Anomaly Detection | ArgoCD | Automated testing | B testing | Behavioral Modeling | CI/CD | Code review | Confidence scoring | Cost monitoring | Datadog APM | Dialogue Management | Drift Detection | Embedding Index | Feature Flags | Feature Store | Gradual Traffic Ramp | Langchain | Low Latency | Low Latency APIs | Model Serving | Online Scoring | OpenSearch | PGVector | Prompt engineering | Python | Retrieval-Augmented Generation | Series analysis | Span Tracing | System design | Threshold Management | Time Series | Time Series Analysis | Vector Search
Education
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