Senior AI Engineer

Posted 13hrs ago

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Job Description

Senior AI Engineer designing, deploying, and optimizing production AI systems for Rearc’s enterprise clients. Building agents, evaluation frameworks, and enterprise integrations.

Responsibilities:

  • Design and implement AI agents, including RAG pipelines, orchestration workflows, and tool invocation
  • Build evaluation frameworks measuring accuracy, latency, cost, and reliability
  • Implement observability and monitoring across the AI system lifecycle
  • Integrate 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 integrated with business workflows
  • Integrate AI systems into enterprise platforms and APIs
  • Debug and optimize live production systems
  • Collaborate with client and internal engineering teams
  • Participate in implementation-focused technical design discussions

Requirements:

  • 4+ years of experience building and deploying AI/ML systems in production
  • 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, including choosing between RAG, agent loops, and workflows
  • Hands-on experience with LLM platforms such as OpenAI, Anthropic, or Google Vertex, and orchestration/harness patterns
  • Proficiency in Python
  • Solid backend engineering skills, including building and deploying APIs, Docker, and cloud-native environments
  • Strong software engineering fundamentals and production-grade coding ability
  • Experience with CI/CD pipelines, infrastructure as code, and production observability
  • Ability to debug and optimize production systems
  • Strong communication skills and ability to explain technical trade-offs to non-technical stakeholders
  • Preferred: familiarity with DSPy, MLflow, promptfoo, RAGAS, or similar evaluation tools
  • Preferred: LLMOps/MLOps experience
  • Preferred: harness engineering experience with Goose, Pi, Claude Code, or Codex
  • Preferred: Databricks experience
  • Preferred: AWS, Azure, or GCP experience
  • Preferred: FastAPI, Pydantic, PostgreSQL, MySQL, or DuckDB experience
  • Preferred: Claude SDK or OpenAI SDK experience
  • Preferred: TypeScript or Go experience
  • Preferred: mentoring or upskilling experience

Benefits:

  • Bonus opportunity of $9.5K–$20.9K
  • Remote work arrangement