Senior Agentic AI Engineer
Tasks
- Analyze post deployment model performance
- Architect API integrations
- Build experimentation frameworks
- Build multi agent collaboration
- Build scalable secure AI systems
- Create dynamic tools
- Deploy AI agents
- Design AI agents
- Develop AI agent architecture
- Develop model lifecycle analytics
- Diagnose data drift root cause
- Enforce clean code standards
- Implement long term memory
- Implement statistical benchmarks
- Improve agile development practices
- Integrate AI agents with enterprise systems
- Lead A/B testing frameworks
- Lead prototypes and proof-of-concepts
- Mentor engineers
- Perform feature engineering
- Perform model debugging
- Test AI agents
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | API Design | AWS | Amazon SageMaker | Artificial Intelligence | Autogen | Azure | B testing | Bayesian Methods | CI/CD | Causal Inference | Cloud Computing | CrewAI | Dask | Data Drift | Experiment design | GCP | GRPC | Git | Hugging Face | Hugging Face Transformers | Langchain | Language Models | Large Language Models | Llamaindex | Machine Learning | Microsoft Semantic Kernel | NumPy | Pandas | Probability | PyTorch | Python | RAG | RESTful APIs | SOLID | SciPy | Scikit-learn | Semantic Kernel | Series analysis | Spark | Statistics | StatsModels | TensorFlow | Time Series | Time Series Analysis | Vector Databases | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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