Lang Chain Deployment AI Engineer
Tasks
- Build LLM powered assistants and copilots
- Create evaluation and quality engineering frameworks
- Create operational documentation and runbooks
- Deploy AI applications with Docker and Kubernetes
- Develop LangGraph agent workflows
- Establish CI CD pipelines for releases
- Implement AI security and responsible AI practices
- Implement LangSmith tracing and evaluation
- Implement rag pipelines
- Integrate LLMs embeddings and vector databases
- Monitor production systems and improve quality and reliability
- Optimize model latency throughput reliability and cost
- Translate AI architectures into production systems
Perks/Benefits
Skills/Tech-stack
AI Search | API Development | AWS | Adversarial Testing | Anthropic | Asynchronous processing | Audit Logging | Azure AI | Azure AI Search | Azure Monitor | CI/CD | Cloud Operations | CloudWatch | Code review | Datadog | Dependency management | Docker | Elasticsearch | Encryption | End to End | End-to-End Testing | Golden datasets | Google Cloud | Google Cloud Operations | Grafana | IAM | Injection Defense | Integration Testing | JavaScript | Kubernetes | LLM | Langchain | Langgraph | Langsmith | Load Testing | Microsoft Azure | Milvus | Model and Prompt Versioning | Monitoring | Observability | OpenAI | OpenSearch | OpenTelemetry | PGVector | Pinecone | Prometheus | Prompt injection | Prompt injection defense | Prompt versioning | Python | RAG | Redis | Retrieval-Augmented Generation | Secrets management | Secure Software | Secure Software Development | Software development | Testing | TypeScript | Unit Testing | Vector Database | Weaviate
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Software Engineer
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