AI Platform Engineer

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: AI Platform Engineer
Location: 100% Remote (Continental United States)
Position Type: Full-time, Direct W2
Salary Range: $100,000 – $150,000 per annum
Experience: 6+ years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary:
We are seeking an AI Platform Engineer to design, build, and operate scalable AI inference platforms for production ML workloads. The ideal candidate will have expertise in distributed systems, LLM serving, GPU optimization, autoscaling, and cloud-native infrastructure, with a strong focus on performance, reliability, and observability.

Key Responsibilities:

• Design and maintain scalable AI model serving platforms.
• Optimize inference performance, GPU utilization, and request routing.
• Build autoscaling, deployment, and monitoring solutions.
• Implement caching, security, and high-availability strategies.
• Collaborate with ML teams to deploy and support production AI models.

Required Qualifications:

• 6+ years of experience in distributed systems, infrastructure, or ML platform engineering.
• Strong proficiency in Python and Go, Rust, or C++.
• Experience with LLM inference frameworks (vLLM, TensorRT-LLM), Kubernetes, cloud platforms, and GPU optimization.

Preferred Qualifications:

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title

AI Platform Engineer

Location: 100% Remote (Continental United States)
Position Type: Full-time, Direct W2
Salary Range: $130,000–$180,000 Annually (based on experience)
Experience Required: 10+ Years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

Bright Vision Technologies is seeking a highly experienced AI Platform Engineer with 10+ years of experience in distributed systems, cloud-native infrastructure, and AI platform engineering to design, build, and operate enterprise-scale AI inference and machine learning platforms. The ideal candidate will possess deep expertise in LLM serving, GPU optimization, Kubernetes, cloud infrastructure, distributed systems, and MLOps, with a proven ability to deliver highly scalable, reliable, secure, and cost-efficient AI platforms supporting production machine learning workloads.

Key Responsibilities

• Design, build, and maintain scalable AI inference and model-serving platforms for enterprise production environments.
• Architect highly available, cloud-native infrastructure supporting Large Language Models (LLMs), foundation models, and machine learning services.
• Optimize inference latency, throughput, GPU utilization, memory management, and request scheduling across distributed AI workloads.
• Design autoscaling, workload orchestration, traffic management, and intelligent request routing strategies for AI services.
• Implement model deployment, versioning, rollback, and lifecycle management using modern MLOps practices.
• Develop monitoring, observability, logging, distributed tracing, and alerting solutions to ensure platform reliability and performance.
• Implement caching strategies, API gateways, security controls, authentication, authorization, and high-availability architectures.
• Collaborate with AI researchers, ML engineers, DevOps teams, and software engineers to deploy and support production AI models.
• Drive cloud infrastructure optimization, resource utilization, FinOps initiatives, and operational excellence.
• Mentor engineering teams, conduct architecture reviews, and establish best practices for AI platform engineering and cloud-native development.
• Evaluate emerging AI infrastructure technologies, model-serving f…