AI Engineer
Fairfax, VA, United States
USD 101K-215K (estimate) Mid-level Full Time
Tasks
- Build prompt pipelines and tool calling workflows
- Collaborate with cross-functional teams in Agile/Scrum
- Deploy AI services and ensure scalability reliability and performance
- Design and build agentic AI systems using LLMs
- Develop and maintain LLM powered applications
- Develop backend services to expose AI capabilities via APIs
- Implement MCP integrations with tools and APIs
- Implement RAG pipelines with vector databases
- Integrate AI solutions with AWS Azure and Google Cloud
- Integrate LLMs into enterprise applications using Spring AI
- Monitor and optimize AI systems for latency cost and output quality
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | AWS Lambda | AWS SageMaker | Agentic Workflows | Agile | Amazon S3 | Azure Cognitive | Azure Cognitive Services | Azure Functions | Azure OpenAI | Cloud BigQuery | Cloud Functions | Cloud deployment | Cognitive Services | Containerization | Docker | Google Cloud | Google Cloud BigQuery | Google Cloud Cloud Functions | Google Cloud Vertex | Google Cloud Vertex AI | Java | LLM APIs | Language Models | Large Language Models | Microservices | Model Context Protocol | Prompt engineering | Python | RAG | REST APIs | Retrieval-Augmented Generation | Scrum | Spring AI | Spring Boot | Structured outputs | Tool-Calling | Vector Databases | Vertex AI
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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