Principal AI Engineer — Enterprise-Scale ML & Production

Netrolynx AI; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

Vanguard seeks a Principal AI Engineer to lead the technical architecture for enterprise‑scale AI and ML platforms, translating cutting‑edge research into production‑grade systems. You will oversee design, deployment, and operational excellence across AI infrastructure and productization efforts.

In this role, you will mentor engineers, shape deployment strategies for LLMs and responsible AI, and drive scalable, observable systems that deliver measurable business value across client solutions.

Qualifications

• Ten or more years of experience in software engineering, ML/AI engineering, or related technical disciplines.
• Deep expertise in designing, deploying, and supporting large-scale AI and ML systems in production.
• Proven success leading complex technical initiatives from concept to deployment and ongoing operations.
• Strong knowledge of software architecture, reliability engineering, observability, ML Ops, DevOps, and cloud technologies.

Responsibilities

• Define and lead the technical architecture for enterprise-scale AI and ML platforms.
• Design scalable, resilient AI systems for mission-critical workloads.
• Establish architectural standards and best practices for AI deployment and operations.
• Drive decisions on model serving, inference optimization, and AI infrastructure.
• Partner with researchers to translate prototypes into production-ready solutions.
• Lead operationalization of AI capabilities across large-scale domains.
• Promote MLOps, LLMOps, and AI platform engineering best practices.
• Mentor engineers and guide architectural reviews and design.

Skills

Senior AI lead

AI architecture

ML Ops

Cloud technologies

Mentoring engineers

Tools

Cloud platforms

MLOps tools

Observability tools

Job description

Vanguard seeks a Principal AI Engineer to lead the technical architecture for enterprise‑scale AI and ML platforms, translating cutting‑edge research into production‑grade systems. You will oversee design, deployment, and operational excellence across AI infrastructure and productization efforts.

In this role, you will mentor engineers, shape deployment strategies for LLMs and responsible AI, and drive scalable, observable systems that deliver measurable business value across client solutions.