AI Developer
Tasks
- Build LLM-powered applications
- Build RAG pipelines
- Build reusable AI components
- Build scalable inference services
- Collaborate with Product teams and Data Scientists
- Conduct code reviews
- Create AI microservices
- Create APIs for AI applications
- Design multi-agent workflows
- Develop end-to-end AI solutions
- Develop prompt strategies
- Implement content filtering
- Implement deployment monitoring
- Implement input sanitization
- Implement predictive machine learning models
- Implement retrieval systems for LLMs
- Implement safety guardrails
- Integrate AI models with enterprise systems
- Integrate with vector databases
- Mentor junior developers
- Optimize model performance
- Perform iterative experimentation and prototyping
- Use evaluation metrics for model quality
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | AWS Glue | AWS Lambda | AWS RDS | AWS RDS PostgreSQL | Airflow | CI/CD | Deep learning | DeepEval | Docker | Embeddings | Few-Shot Learning | Few-shot | Git | Graph Databases | Graph RAG | Jenkins | Kubernetes | LLM Evaluation | LLM orchestration | Langchain | Langgraph | Llamaindex | Logging | Machine Learning | N8n | Neo4j | Observability | OpenSearch | PGVector | Prefect | Prompt engineering | Python | RAG | RDS PostgreSQL | REST APIs | Ragas | Retrieval-Augmented Generation | Serverless | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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