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# Senior AI Engineer

- **Company:** REARC LLC
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Abstraction Layers, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Software Debugging, High-Level Architecture, Python (Programming Language), PostgreSQL, MySQL, Regression Testing, OpenAI, Software Engineering, Software Systems, System Testing, TypeScript, Scripting, Retrieval-Augmented Generation, DSPy (Programming Framework), Large Language Models, Claude Code, Agentic-AI, Fastapi, Build Management, Low Latency, Production Code, RAGAS (Retrieval Augmented Generation Assessment), Machine Learning Operations, Claude, Promptfoo, Docker, Databricks, Programming Languages
- **Published:** November 12, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-ai-engineer--eb7c5a14-9da9-4b95-89fe-92732153d078

## About the Role

Artificial Intelligence (AI), Problem Solving Skills, Product Development, Software Engineering, Prototyping, Product Lifecycle, Scripting (Scripting Languages), Artificial Intelligence (AI), Resolve Customer Issues, Production Systems, * 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

Preferred Experience

 * Familiarity with prompt optimization or evaluation tools (DSPy, MLflow, promptfoo, RAGAS, etc.)
 * LLMOps/MLOps experience: building robust, monitored, self-healing AI systems
 * Experience with harness engineering (e.g., developing on/with Goose, Pi, Claude Code, Codex)
 * Databricks experience (preferred)
 * Experience with cloud platforms such as AWS, Azure, or GCP
 * Experience with FastAPI, Pydantic, PostgreSQL, MySQL, or DuckDB
 * Experience using the Claude SDK or OpenAI SDK
 * Additional programming languages beyond Python-TypeScript or Go are strong positives
 * Experience mentoring or upskilling fellow engineers

## Description

* 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 optimize live production systems
 * Collaborate closely with both client and internal engineering teams
 * Participate in technical design discussions with a focus on implementation