Job Description

LockedIn AI is hiring an AI Cloud Engineer to design, build, and optimize the cloud infrastructure powering our real-time AI systems used by over 1 million users worldwide.

This is a high-impact infrastructure role at the intersection of cloud engineering and AI systems, where you will architect scalable GPU-based environments for training, inference, and deployment of large-scale AI models.

About the Role

We are looking for a cloud-native AI infrastructure engineer who understands both distributed systems and AI workloads.

You will own the cloud foundation that powers our AI interview copilot platform — ensuring low-latency inference, scalable GPU compute, efficient training pipelines, and cost-optimized AI infrastructure.

This role is critical in enabling fast, reliable, and scalable AI experiences for millions of users.

Key Responsibilities

AI Cloud Architecture

• Design scalable cloud infrastructure for AI/ML workloads
• Build GPU-based training and inference environments
• Architect multi-stage AI environments (dev, staging, production)
• Optimize for latency, scalability, and reliability

Model Serving & Inference

• Deploy and manage LLM inference systems (vLLM, Triton, TGI, etc.)
• Optimize real-time AI response performance
• Implement load balancing, routing, and failover systems
• Ensure high availability for millions of users

GPU & Training Infrastructure

• Manage GPU clusters for training and fine-tuning models
• Implement distributed training pipelines
• Optimize GPU utilization and compute efficiency
• Manage cloud AI services (SageMaker, Vertex AI, Azure ML, etc.)

Cost Optimization (FinOps for AI)

• Monitor and reduce cloud and GPU costs
• Optimize inference and training expenses
• Build dashboards for cost tracking and usage analysis
• Improve token and compute efficiency

Security & Networking

• Design secure cloud architecture for AI systems
• Implement IAM, encryption, and access controls
• Manage VPCs, networking, and private endpoints
• Ensure compliance readiness (SOC2, GDPR, etc.)

Automation & Observability

• Build Infrastructure as Code using Terraform or similar tools
• Implement CI/CD pipelines for cloud infrastructure
• Monitor GPU health, latency, and system performance
• Set up alerts for failures and anomalies

Requirements

Experience

• 3+ years in cloud engineering, DevOps, or infrastructure roles
• Experience with AI/ML infrastructure or GPU workloads
• Hands-on experience with production cloud systems
• Experience working in fast-paced startup environments

Technical Skills

• Strong cloud experience (AWS / GCP / Azure)
• Kubernetes and container orchestration expertise
• Experience with model serving frameworks (vLLM, Triton, etc.)
• Infrastructure as Code (Terraform, Pulumi, CloudFormation)
• Monitoring tools (Prometheus, Grafana, Datadog, etc.)
• Python, Go, or Bash scripting

Soft Skills

• Strong systems thinking and problem-solving ability
• Cost-conscious engineering mindset
• Clear communication and documentation skills
• Ability to work independently in high-ownership environments

Preferred Qualifications

• Experience with large-scale LLM inference systems
• Knowledge of distributed training and multi-GPU systems
• Experience with real-time AI or streaming systems
• Familiarity with RDMA / high-performance networking
• Open-source contributions in AI infrastructure
• Startup or early-stage company experience

Compensation

$140,000 – $195,000 USD / year
Remote (US-based) with optional hybrid in New York, NY

What We Offer

• Equity: Meaningful ownership in a fast-growing AI company
• Impact: Your work powers systems used by 1M+ users
• Flexibility: Remote-first with optional NYC collaboration
• Growth: Work on cutting-edge AI infrastructure at scale
• Culture: Fast execution, high ownership, AI-native environment

Why Join Us

• Build the cloud infrastructure behind real-time AI systems
• Work directly with cutting-edge LLM and GPU workloads
• Solve high-scale engineering problems in production AI
• Shape the foundation of a category-defining AI platform

How to Apply

Please submit:

• Resume / CV
• Short note on why you want to join
• Whether you’ve used the product
• Optional: GitHub, cloud projects, or technical writing

Skills Required

• cloud engineering