Lead Engineer, Agentic AI Systems - Remote & Impactful

Jobgether SRL

United States

Remote

USD 122,000 - 214,000

Full time

3 days ago
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Benefits offered by this job

Remote work
20% annual bonus
401(k) match
Parental leave
EAP program

Job summary

Lead Engineer - Agentic AI Systems based in the United States oversees the infrastructure powering enterprise AI, ML, and agentic solutions at scale. You will define technical strategy, system architecture, and deployment models across cloud, edge, and on-prem environments.

You will mentor engineers, drive architectural standards, and partner with IT, security, and hardware teams to deliver scalable model-serving, MLOps/LLMOps, and secure, cost-aware AI platforms powering real-world business

Qualifications

  • Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field with 5+ years in systems engineering.
  • Master's degree in CS or related discipline preferred.
  • Experience architecting multi-region cloud infrastructures and edge/cloud deployments.
  • Proven leadership, vendor interaction, and complex tech decision-making.

Responsibilities

  • Define enterprise technical strategy, hardware roadmaps, and deployment architectures for AI compute infra.
  • Lead architectural investigations, capacity planning, and system benchmarking for AI workloads.
  • Design scalable model-serving, MLOps/LLMOps platforms across cloud and edge environments.
  • Guide cross-functional teams, set technical direction, and ensure enterprise standards.

Skills

Leadership
Communication
Strategic thinking

Education

Bachelor's degree in Computer Engineering/CS
Master's degree preferred

Tools

Kubernetes
GKE
Python
Containerization

Job description

Lead Engineer - Agentic AI Systems based in the United States oversees the infrastructure powering enterprise AI, ML, and agentic solutions at scale. You will define technical strategy, system architecture, and deployment models across cloud, edge, and on-prem environments.

You will mentor engineers, drive architectural standards, and partner with IT, security, and hardware teams to deliver scalable model-serving, MLOps/LLMOps, and secure, cost-aware AI platforms powering real-world business

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