AI Engineer
Mid-level Full Time
Tasks
- Apply machine learning concepts for model evaluation and improvement
- Build MCP servers and tools for LLM integrations
- Build integrations with APIs databases and cloud services
- Create AI agents and orchestration pipelines
- Design AI automation solutions using large language models
- Design and query knowledge graphs
- Develop backend logic data pipelines and automation scripts using Python
- Develop prompt engineering strategies for production workflows
- Document AI automation solutions and technical decisions
- Ensure AI solutions security scalability explainability and maintainability
- Support deployment monitoring testing and troubleshooting
- Translate business requirements into AI technical solutions
- Write and optimize SQL queries for data workflows
Perks/Benefits
- N/A
Skills/Tech-stack
AI Agents | API Gateway | AWS | AWS Glue | AWS Lambda | AWS Neptune | AWS Step Functions | Access Control | Airflow | Amazon Athena | Amazon Bedrock | Amazon ECS | Amazon EKS | Amazon S3 | Amazon SageMaker | Auditability | Autogen | Azure | CI/CD | Classification | CloudWatch | Clustering | Compliance | CrewAI | Data Privacy | Data Quality | Django REST | Django REST Framework | Docker | ETL/ELT | FastAPI | Feature Engineering | Flask | Generative AI | Git | Governance | IAM | Knowledge graphs | Langchain | Language Models | Large Language Models | Latency monitoring | Llamaindex | Logging | Machine Learning | Model Context Protocol | Model Evaluation | N8n | Observability | OpenSearch | Power Automate | Prompt engineering | Python | REST APIs | REST Framework | Regression | Responsible AI | Retrieval-Augmented Generation | SQL | Security | Semantic Kernel | ServiceNow | Step Functions | Tracing | Usage analytics | Zapier
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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