Agentic AI Engineer
Tasks
- Apply data privacy and security best practices
- Apply prompt engineering
- Build LLM based agent workflows
- Build text classification and intent recognition systems
- Create vector database and embeddings integrations
- Deploy containerized AI services
- Design autonomous AI systems
- Develop NLP and generative AI applications
- Develop information extraction solutions
- Implement MLOps and LLMOps pipelines
- Implement fine-tuning
- Implement intelligent automation solutions
- Implement planning and tool use
- Implement rag pipelines
- Integrate external services via APIs
- Orchestrate multi-step agent workflows
Perks/Benefits
- Career plan
- Company equipment
- Knowledge sharing
- Learning opportunities
- Mentorship
- Option for Co Ownership
- Team activities
Skills/Tech-stack
API Integration | Agentic Systems | Autogen | Data Privacy | Docker | Embeddings Models | Fine Tuning | Generative AI | Hugging Face | Information Extraction | Intent Recognition | Kubernetes | LLMOps | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Llamaindex | MLOps | Natural Language | Natural Language Processing | Prompt engineering | RAG | Retrieval-Augmented Generation | Semantic understanding | Text Classification | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Agentic AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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