AI Solutions Engineer
Tasks
- Build and optimize RAG pipelines with enterprise knowledge sources
- Build scalable AI workflows for enterprise automation
- Collaborate with product engineering and business teams to deliver AI solutions
- Design and deploy AI agents using LLMs and RAG
- Design evaluation frameworks for quality retrieval accuracy and hallucination risk
- Develop reusable prompt workflows and structured outputs
- Implement secure tool calling capabilities
- Improve retrieval quality using chunking embeddings and indexing
- Integrate AI applications with enterprise systems APIs and databases
- Monitor and optimize AI application performance
- Optimize prompts guardrails and model performance
- Support UAT production rollout and technical documentation
- Support governance version control and human in the loop review
Perks/Benefits
- N/A
Skills/Tech-stack
AI Agents | APIs | AWS Bedrock | Azure OpenAI | CI/CD | Containerization | Databases | Domain Adaptation | Fine Tuning | Git | Google Vertex | Google Vertex AI | Human-in-the-loop | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | MLOps | Model Context Protocol | Model Fine-tuning | Ollama | Prompt engineering | Python | RAG Pipelines | Retrieval-Augmented Generation | Semantic Search | The Loop | VLLM | Vector Databases | Vertex AI
Education
Roles
AI | AI Solutions | AI Solutions Engineer | Engineer | Solutions Engineer
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