ML Solutions Architect
Tasks
- Advise build vs buy decisions
- Architect Agentic AI solutions
- Collaborate with delivery teams for handoff
- Create reference architectures for RAG agents
- Create technical proposals and presentations
- Demonstrate ML and agentic capabilities
- Design MCP integration strategies
- Design end-to-end ML architectures
- Develop agentic POC demonstrations
- Develop reusable solution patterns
- Estimate project scope and timelines
- Lead pre sales technical discovery
- Mentor engineers on client communication
- Present solutions to technical and non-technical audiences
- Provide technical guidance during execution
- Recommend agent frameworks
- Serve as client technical point of contact
Perks/Benefits
- Conference attendance
- Learning budget
- Professional development subscriptions
- Regular client travel opportunities
- Remote-first
Skills/Tech-stack
API Gateway | AWS API | AWS API Gateway | AWS ECS | AWS Lambda | AWS SageMaker | AWS Step Functions | Agent systems | AgentOps | Agentic AI | Amazon Bedrock | Cloud Security | Cost Optimization | Data Lakes | Data Monitoring | Data Pipelines | Data Validation | Data Warehousing | ELT | ETL | Function Calling | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Context Protocol | Multi-Agent | Multi-Agent Systems | Privacy Compliance | RAG | Step Functions | System design | Tool-Calling | Vector Databases
Education
N/A
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