AI Solutions Engineer
Tasks
- Build RAG data pipelines
- Build connectors for analytics services
- Build real time data connectors
- Develop MCP servers
- Develop microservices
- Develop secure REST APIs
- Identify opportunities to reduce manual workflows using AI tools
- Implement grounding techniques
- Improve AI usability explainability and relevance
- Improve accuracy using prompt engineering
- Integrate LLMs with enterprise document stores
- Integrate virtualized data sources into AI workflows
- Monitor AI performance
- Optimize RAG retrieval performance
- Reduce LLM token usage
- Transform data for LLM consumption
Perks/Benefits
- 401k
- Education reimbursement
- Flexible benefits package
- Flexible schedule
- Hybrid work schedule
- Relocation assistance
- US federal security clearance support
Skills/Tech-stack
Agile | CI/CD | Cloud Computing | Containerization | Guardrails | Java | JavaScript | Knowledge graphs | Language Models | Large Language Models | MCP | Microservices | Prompt Tuning | Prompt engineering | Python | REST API | Retrieval-Augmented Generation | Scrum | Secure APIs | Semantic Search | TypeScript | Vector Databases | Vector embeddings
Education
Roles
AI | AI Solutions | AI Solutions Engineer | Engineer | Software Engineer | Solutions Engineer
Regions
Countries
States
Cities
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