Lead Architect
Tasks
- Automate LLMOps platforms for enterprise GenAI systems
- Build LLMOps lifecycle automation and observability
- Build agentic AI workflows and evaluation capabilities
- Create end to end LLM pipelines for data ingestion embeddings evaluation inference
- Deploy AI services using cloud and on premises DevOps practices
- Design deploy scale GenAI and agentic AI applications
- Develop model training and deployment at scale
- Implement LLM infrastructure memory management token control prompt chaining context optimization
- Implement guardrails output filtering context aware routing incident response
- Optimize performance for production workloads
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | AWS Bedrock | AWS SageMaker | Airflow | Azure ML | Bash | BentoML | Delta Lake | Docker | FastAPI | Feast | Feature Store | Fine Tuning | Flink | GCP Vertex | GCP Vertex AI | GPU scaling | GitOps | Helm | Kubernetes | LLM Evaluation | Lakehouse | Langchain | Langfuse | Langtrace | Language Processing | Llamaindex | MLflow | Model Fine-tuning | NLP | Natural Language | Natural Language Processing | Observability | Output filtering | PEFT | Parquet | Prefect | Prompt Chaining | Prompt engineering | Python | RAG | Ray | Spark | Terraform | Terraform HCL | Token Control | Vector Databases | Vertex AI | YAML
Education
N/A
Roles
AI | AI Solutions | AI Solutions Architect | Architect | Lead | Lead Architect | Solutions Architect
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