Senior AI Engineer - Production ML Systems

Rearc; Oregon; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Rearc is seeking a hands-on AI Engineer to design, build, and deploy production-grade AI systems within enterprise environments. This role focuses on delivering real-world AI/ML solutions that address actual customer needs beyond demos or notebooks.

You will work across the full development lifecycle, from system design to production deployment, shipping robust AI-powered applications that integrate into business workflows.

Qualifications

• 4+ years of experience building and deploying AI/ML systems in production (beyond demos or experimentation).
• Track record of architecting, building, and successfully shipping AI/ML or software solutions using modern AI-assisted workflows.
• Strong understanding of AI system evaluation and measurement: including offline metrics, online monitoring, LLM-as-judge processes, regression testing, and cost/latency tracking.
• Practical judgment in retrieval and agent design trade-offs, with the ability to explain and choose between RAG, agent loops, and workflows as needed.
• Hands-on experience with LLM platforms (OpenAI, Anthropic, Google Vertex, or similar) and orchestration/harness patterns.
• Proficiency in Python, which forms the foundation of our engineering efforts.
• Solid backend engineering skills: building and deploying APIs, working with Docker, and navigating cloud-native environments (containers, basic infrastructure).
• Strong software engineering fundamentals: you write maintainable, production-grade code, not just wire together demos.
• Experience with CI/CD pipelines, infrastructure as code, and production observability.
• Ability to debug and optimise systems already in production.
• Strong communication skills, including the ability to explain technical trade-offs to non-technical stakeholders.

Responsibilities

• Design and implement AI agents, including RAG pipelines, orchestration workflows, and tool invocation.
• Build evaluation frameworks to measure system accuracy, latency, cost, and reliability.
• Implement observability and monitoring across the AI system lifecycle.
• Integrate with multiple AI providers and develop abstraction layers for multi-model architectures.
• Optimize AI systems for performance, cost, and scalability.
• Build and deploy AI-powered applications tightly coupled with real business workflows.
• Integrate AI systems into existing enterprise platforms and APIs.
• Debug and optimise live production systems.
• Collaborate closely with both client and internal engineering teams.
• Participate in technical design discussions with a focus on implementation.

Skills

AI/ML systems

Production deployment

Python

Backend APIs

Docker

CI/CD

Cloud platforms

LLMOps

RAG & agents

Performance optimization

Communication

Tools

OpenAI

Anthropic

Google Vertex

Goose

Claude SDK

OpenAI SDK

DSPy

MLflow

promptfoo

Job description

Rearc is seeking a hands-on AI Engineer to design, build, and deploy production-grade AI systems within enterprise environments. This role focuses on delivering real-world AI/ML solutions that address actual customer needs beyond demos or notebooks.

You will work across the full development lifecycle, from system design to production deployment, shipping robust AI-powered applications that integrate into business workflows.