AI Engineer | Mid
Tasks
- Apply LLMOps practices for monitoring and continuous improvement
- Build secure integrated AI applications
- Create intelligent document processing and classification systems
- Define solution architectures for security scalability and observability
- Deploy and manage AI applications on cloud AI platforms
- Design develop and deploy generative AI solutions at scale
- Develop intelligent agents with large language models
- Implement retrieval augmented generation and chatbot solutions
- Orchestrate agent workflows and build API integrations
- Perform testing optimization and engineering best practices
Perks/Benefits
- Career development
- Collaborative knowledge sharing
- Fully remote work
- Professional growth opportunities
Skills/Tech-stack
AI platforms | API Integration | AWS Bedrock | Agent Orchestration | Azure OpenAI | Chatbots | Classification Systems | Cloud AI | Cloud AI Platforms | Cypher | Document processing | Generative AI | Git | Graph Modeling | Intelligent Document Processing | LLMOps | LangFlow | Langchain | Langgraph | Language Models | Large Language Models | MCP | Model Context Protocol | Monitoring | Neo4j | Observability | Retrieval-Augmented Generation | Solution architecture | Testing | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer
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