Lead AIML Engineer
Tasks
- Architect scalable secure multi tenant SaaS platforms
- Build PII detection anonymization and de anonymization pipelines
- Build and deploy agentic AI systems with agent frameworks
- Build scalable multi tenant SaaS architectures
- Define best practices for LLM integration and agent orchestration
- Design human-in-the-loop workflows
- Design secure access controls and data protection
- Develop MCP servers
- Develop cloud native AI applications
- Drive AI observability tracing reliability and compliance
- Ensure compliance with security standards
- Establish LLM governance cost optimization rate limiting monitoring audit trails
- Implement AI guardrails against prompt injection data leakage and hallucination
- Implement CI CD automation with infrastructure as code
- Implement Retrieval-Augmented Generation (RAG)
- Implement function calling
- Implement structured extraction
- Integrate LLMs using cloud AI platforms
- Lead design and development of agentic AI workflows
- Mentor teams on agentic AI and LLM development practices
- Provide technical demonstrations and RFP RFI responses
- Support customer technical discovery and solution discussions
Perks/Benefits
- N/A
Skills/Tech-stack
AI Foundry | AWS | AWS Bedrock | AWS EKS | AWS Lambda | Agno | Amazon RDS | Amazon S3 | Anonymization | Autogen | Azure | Azure AI | Azure AI Foundry | CI/CD | CrewAI | Data extraction | De Anonymization | Docker | Document processing | Function Calling | GCP | GitHub Actions | Guardrails AI | Intelligent Document Processing | Kubernetes | Langgraph | Model Context Protocol | Multi-tenant | Multi-tenant architecture | Nemo Guardrails | Object storage | PGVector | PII Detection | Pinecone | Prompt engineering | Python | Qdrant | Retrieval-Augmented Generation | SQL | Semantic Kernel | Structured data | Structured data extraction | Tenant architecture | Terraform | Vector Databases | Vertex AI | Weaviate
Education
N/A
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