AI Engineer - Application Development
Tasks
- Address security vulnerabilities and cybersecurity compliance
- Apply prompt engineering strategies
- Build RAG pipelines
- Build and maintain web applications
- Design AI enabled features for web workflow applications
- Develop full stack AI features with API integrations
- Document technical implementations and track AI ML developments
- Implement LLM observability and responsible AI guardrails
- Implement agentic workflows with orchestration frameworks
- Integrate AI/LLM APIs
- Participate in code reviews and CI/CD pipelines
Perks/Benefits
Skills/Tech-stack
API Integration | AWS | Agno | Amazon Bedrock | Azure | CI/CD | Chain-of-Thought | Cloud platform | CrewAI | Docker | Feature Engineering | Few-Shot Prompting | Few-shot | Git | Google Cloud | Google Cloud Platform | Haystack | JavaScript | LLM Observability | LLM orchestration | Langgraph | Machine Learning | Model Evaluation | NLP | Node.js | NumPy | OpenAI API | Pandas | Prompt engineering | Python | RESTful API | RESTful API Integration | RESTful APIs | React | Retrieval-Augmented Generation | Scikit-learn | Supervised Learning | System prompts | TypeScript | Unsupervised Learning | Vector Databases
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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