AI Platform Engineer & Architect

Ethereum Technologies LLC; Concord (CA); On-site; USD 83,000 - 113,000; Full time

Job summary

Ethereum Technologies in Concord, CA is seeking an AI Platform Engineer & Architect for a 12-month contract to design, implement, and optimize production-grade model-serving platforms. The role focuses on real-time inference, scalable AI/ML services, and tightly integrated CI/CD workflows across Kubernetes-based environments.

You will collaborate with Data Science, Platform Engineering, MLOps, and Infra teams to ensure reliable operations, observability, and secure deployments, while driving

Qualifications

• Experience with online inference and production model-serving architectures.
• Real-time APIs and distributed systems design.
• Proficiency in Python, Java, Go, or similar backend languages.
• Experience operating in cloud-based and on-prem environments.

Responsibilities

• Design and implement highly available, low-latency model-serving architectures for real-time inference workloads.
• Develop and standardize deployment patterns for scalable AI/ML services across Kubernetes-based platforms.
• Lead API-based inference service design, integration, deployment, and lifecycle management.
• Optimize model-serving performance through latency tuning, caching, autoscaling, and resource management.
• Establish monitoring, observability, SLOs/SLAs, alerting, and runbooks for production services.
• Drive load testing, capacity planning, resiliency engineering, and disaster recovery readiness.
• Integrate inference platforms with CI/CD pipelines to enable automated deployments and controlled releases.
• Collaborate with Data Science, Platform Engineering, MLOps, and Infrastructure teams for reliable production model ops.
• Establish operational best practices, security standards, reliability measures, and performance benchmarks for enterprise AI deployments.

Skills

Kubernetes

Real-time APIs

Distributed systems

Autoscaling

Performance engineering

Monitoring & observability

CI/CD

IaC

Cloud & on-prem

Backend languages (Python/Java/Go)

Tools

Kubernetes

Docker

Terraform

Prometheus/Grafana

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: AI Platform Engineer & Architect
Location: Concord, CA
Duration: 12 Months + Extension
Bill Rate: $71/hour
Job Type: W-2 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Key Responsibilities

Design and implement highly available, low-latency model-serving architectures for real-time inference workloads.

Develop and standardize deployment patterns for scalable AI/ML services across Kubernetes-based platforms.

Lead API-based inference service design, integration, deployment, and lifecycle management.

Optimize model-serving performance through latency tuning, caching strategies, autoscaling, and resource management.

Establish monitoring, observability, SLOs/SLAs, alerting, and operational runbooks for production services.

Drive load testing, capacity planning, resiliency engineering, and disaster recovery readiness.

Integrate inference platforms with CI/CD pipelines to enable automated deployments and controlled releases.

Collaborate with Data Science, Platform Engineering, MLOps, and Infrastructure teams to ensure reliable production model operations.

Establish operational best practices, security standards, reliability measures, and performance benchmarks for enterprise AI deployments.

Job Title: AI Platform Engineer & Architect
Location: Concord, CA
Duration: 12 Months + Extension
Bill Rate: $71/hour
Job Type: W-2 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Key Responsibilities

• Design and implement highly available, low-latency model-serving architectures for real-time inference workloads.
• Develop and standardize deployment patterns for scalable AI/ML services across Kubernetes-based platforms.
• Lead API-based inference service design, integration, deployment, and lifecycle management.
• Optimize model-serving performance through latency tuning, caching strategies, autoscaling, and resource management.
• Establish monitoring, observability, SLOs/SLAs, alerting, and operational runbooks for production services.
• Drive load testing, capacity planning, resiliency engineering, and disaster recovery readiness.
• Integrate inference platforms with CI/CD pipelines to enable automated deployments and controlled releases.
• Collaborate with Data Science, Platform Engineering, MLOps, and Infrastructure teams to ensure reliable production model operations.
• Establish operational best practices, security standards, reliability measures, and performance benchmarks for enterprise AI deployments.

Required Technical Skills

• Strong experience with online inference and production model-serving architectures.
• Expertise in real-time APIs and distributed systems design.
• Hands-on experience with Kubernetes, container orchestration, and service mesh technologies.
• Knowledge of autoscaling, capacity management, and workload optimization.
• Experience in performance engineering, load testing, and latency optimization.
• Strong understanding of monitoring, observability, logging, distributed tracing, and SLO management.
• Experience with CI/CD, DevOps, and Infrastructure as Code (IaC).
• Knowledge of reliability engineering, fault tolerance, and resiliency patterns.
• Experience operating cloud-based and on-premises platforms.
• Proficiency in Python, Java, Go, or similar backend programming languages.

Preferred Qualifications

• Experience with MLOps platforms and enterprise AI deployment frameworks.
• Hands-on experience with real-time recommendation, fraud detection, risk assessment, personalization, or predictive analytics platforms.
• Familiarity with GPU-based inference, model optimization, and multi-cloud deployments.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.