Related skills
langchain langgraph sagemaker mcp github copilot📋 Description
- Lead technical discovery sessions with prospective clients.
- Translate client problems into ML solutions and design end-to-end ML architectures.
- Create compelling technical presentations and demonstrations; estimate scope, timelines, cost.
- Serve as primary technical contact for clients; manage stakeholder expectations.
- Architect agentic AI solutions with autonomous decision-making and tool orchestration.
- Design MCP integration strategies and evaluate agent frameworks for client use cases.
🎯 Requirements
- Architect end-to-end ML systems; scalable, production-grade.
- ML lifecycle: data to deployment.
- System design: scalable, production-grade ML architectures; trade-off analysis.
- Agentic AI: agent patterns, tool orchestration; MCP proficiency.
- Claude ecosystem: Claude Code, Claude Agent SDK; LangGraph/LangChain.
- AWS/cloud: SageMaker, Bedrock; Lambda, ECS; security/compliance.
- Data pipelines, storage, quality; real-time vs batch design.
🎁 Benefits
- High-visibility role with diverse clients.
- Shape solution offerings and practice direction.
- Work with cutting-edge ML, LLM, and agentic AI tech.
- Global exposure across LATAM, Europe, and North America.
- Remote-first with client travel; path to leadership.
- Learning budget and conference attendance; access to AI tools.
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