AI Engineer Sr
Tasks
- Apply guardrails permissions audit trails and fallback mechanisms
- Build LLM embeddings and vector search solutions
- Create agentic workflows and AI orchestration patterns
- Deploy and operate AI solutions in cloud environments
- Design develop test deploy AI powered applications
- Establish CI CD observability and secure development practices
- Evaluate AI models for accuracy performance scalability privacy and cost
- Implement responsible AI controls for privacy security auditability and data protection
- Implement retrieval augmented generation systems
- Integrate AI agents with enterprise APIs and business applications
- Mitigate risks including hallucinations bias misuse and data leakage
- Monitor performance reliability usage costs and quality
- Provide technical guidance and lead AI architecture discussions
Perks/Benefits
Skills/Tech-stack
AI Observability | AI Search | AI orchestration | API Development | Agentic Workflows | Autogen | Automated testing | Azure AI | Azure AI Search | Azure OpenAI | C# | CI/CD | CrewAI | Data Pipelines | Elasticsearch | Embeddings | Experiment tracking | Generative AI | Go | Hugging Face | Java | LLM Evaluation | Langchain | Language Models | Large Language Models | Llamaindex | Monitoring | Observability | OpenAI APIs | OpenSearch | Pinecone | Prompt engineering | Prompt management | Python | Quality monitoring | Retrieval Quality | Retrieval Quality Monitoring | Retrieval-Augmented Generation | Secure Development | Semantic Kernel | Structured data | System design | Token Usage Monitoring | Token usage | TypeScript | Unstructured Data | Usage monitoring | Vector Databases | Vector Search
Education
N/A
Roles
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