Lead Engineer - Agentic AI Systems

Jobgether SRL; United States; Remote; USD 122,000 - 214,000; Full time

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

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Engineer - Agentic AI Systems based in United States.

This is a strategic engineering leadership role responsible for shaping the infrastructure that powers enterprise AI, machine learning, and agentic solutions at scale. You will define technical strategy, system architecture, hardware roadmaps, and deployment models spanning cloud environments, high-performance AI infrastructure, and distributed edge fleets. The role combines hands-on architectural leadership with long-term planning around reliability, security, performance, and cost optimization. You will help build scalable model-serving and MLOps/LLMOps platforms that support real-world business operations and AI-enabled experiences. Working across infrastructure, security, IT, hardware, and AI teams, you will establish technical standards and guide multiple concurrent initiatives. This is an opportunity to influence the evolution of a large-scale AI ecosystem while mentoring engineers and driving adoption of emerging technologies.

• Define the enterprise technical strategy, hardware roadmaps, and deployment architectures for distributed AI compute infrastructure, cloud platforms, and store-level edge environments.

• Establish technical standards for infrastructure reliability, disaster recovery, hardware security, and compute cost governance across AI platforms and deployments.

• Lead architectural investigations, capacity planning exercises, and system benchmarking for next-generation AI workloads, multimodal models, and low-latency edge inference.

• Design scalable model-serving, MLOps, and LLMOps infrastructure that enables AI, machine learning, and agentic solutions to operate reliably across enterprise environments.

• Partner with Enterprise IT, Security, cross-functional stakeholders, and hardware vendors to develop network topologies, edge hardware specifications, secure API gateways, and deployment architectures.

• Evaluate cloud infrastructure providers, GPU vendors, and edge hardware manufacturers, supporting vendor selection and negotiating technical requirements and service-level agreements.

• Drive infrastructure right-sizing, security improvements, performance optimization, and cost efficiency across AI compute environments.

• Provide technical oversight and architectural review across infrastructure and AI engineering initiatives, ensuring consistency with enterprise standards and long-term strategy.

• Establish scalable frameworks, engineering best practices, and technology standards for the development and operation of AI platforms.

• Lead and mentor cross-functional engineering teams, set technical direction, and guide delivery across multiple concurrent strategic initiatives.

Requirements:

• A Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field, combined with 5+ years of experience in systems engineering, cloud architecture, and infrastructure leadership.

• A Master’s degree in Computer Science or a related discipline is preferred.

• Demonstrated experience architecting multi-region cloud infrastructures, hybrid edge-cloud networks, and large-scale Kubernetes or GKE deployment fleets.

• A strong track record of leading complex engineering initiatives, establishing technical vision, and influencing significant technology investments and vendor decisions.

• Deep knowledge of heterogeneous compute environments, including GPU, NPU, and TPU architectures, as well as low‑latency networking, distributed storage, and inference acceleration runtimes.

• Proficiency with Python, Kubernetes and containerization technologies, along with major cloud platforms such as GCP, Azure, or AWS.

• Strong understanding of scalable AI infrastructure, model serving, MLOps/LLMOps, and the operational requirements of modern AI and agentic systems.

• Excellent architectural, analytical, and problem‑solving abilities, with the capacity to balance performance, reliability, security, scalability, and cost.

• Strong leadership and communication skills, with experience providing technical direction, mentoring engineers, and collaborating across infrastructure, security, IT, AI, and external vendor teams.

• Previous experience in the food service or a related industry is preferred.

Benefits:

• Base salary ranging from $122,000 to $214,000 per year, depending on factors such as experience, skills, knowledge, internal equity, and business considerations.

• Target annual bonus of 20% of annualized base salary, based on company and individual performance.

• Primarily remote work arrangement, with travel to designated company locations or other sites as business needs require.

• Company 401(k) match.

• Parental leave.

• Access to Employee Assistance Program (EAP) sessions.

• Eligibility for additional benefits and incentives offered through the company’s applicable benefit plans and policies.