AI Deployment Engineering Manager (all genders)
Core
Technical owner embedding into client organizations to scope problems, build AI-native solutions, and manage production deployment of AI systems.
Role type
Senior IC AI Deployment Engineering Manager
Builds
Production-grade AI applications, custom agents, LLM-powered workflows, and agent skills integrated into client technology estates.
Domain
Enterprise AI, Cloud Infrastructure, Full-Stack Engineering
Deliverable
production ML models
Required skills
Python, TypeScript or Java, Cloud platforms (AWS, GCP, Azure), CI/CD, Infrastructure-as-Code (Terraform, Helm), Containerization (Kubernetes, Docker), Data Engineering, AI/ML frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen), Vector databases, Semantic search, Rapid prototyping, Systems integration, Technical storytelling, Cross-functional communication
Preferred skills
FDE model experience (MCP servers, sub-agents, agent skills), Responsible AI implementation, Design literacy, Client capability building
Technologies
Python, TypeScript, Java, AWS, GCP, Azure, Terraform, Helm, Kubernetes, Docker, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Vector databases
Responsibilities
Design and ship production-grade AI applications inside client systems; Own the complete delivery stack from backend logic to front-end surfaces; Compress the gap between concept and working software; Connect AI-native capabilities to client existing platforms; Operate inside client environments as a trusted technical partner; Scope messy, under-defined problems into tractable engineering challenges; Monitor, debug, and optimize deployed systems; Translate complex AI behaviors into transparent user experiences; Communicate technical trade-offs to engineering teams and executive stakeholders; Document architectures and deployment patterns for practice scaling; Run workshops to transfer knowledge to client teams.
Seniority
Senior, hands-on IC with client-facing delivery ownership
