Senior Applied Artificial Intelligence Engineer

Role overview

Senior Applied Artificial Intelligence Engineer (Senior individual contributor, full remote). Design and build reusable AI systems—especially LLM and agent-based workflows—then translate ideas into modular components that can be integrated into production via APIs.

Responsibilities

• Design and build reusable AI systems to accelerate innovation across the organization
• Rapidly prototype LLM and agent workflows (pragmatic tradeoffs, bias for action)
• Convert strategies and concepts into structured, modular systems that production engineering teams can adopt or consume through well-defined APIs
• Partner with specialty data science teams and the Head of AI to operationalize models and shape AI technical direction
• Provide end-to-end ownership of projects: from prototyping through clean handoff to production

Requirements

• SQL proficiency, including intermediate querying and basic ETL jobs
• 6+ years in software engineering or machine learning engineering building backend/distributed systems
• Strong Python skills for modular, testable, well-structured codebases
• Hands-on LLM application development, including:
  • RAG pipelines
  • Prompt orchestration
  • Structured outputs
  • Tool-calling workflows
• Familiarity with agent frameworks/orchestration libraries (e.g., LangChain, LlamaIndex, Semantic Kernel, or similar)
• Experience with vector databases and retrieval strategy design
• Ability to integrate ML/statistical model outputs into production-oriented systems
• Experience designing and exposing RESTful and/or event-driven APIs
• Understanding of LLM evaluation concepts (e.g., prompt versioning, offline evals, feedback loops, guardrails)
• Comfort operating in ambiguity and driving initiatives end-to-end with minimal oversight
• Experience with rapid prototyping and deployment ecosystems
• Cloud familiarity (AWS preferred), Docker, and deployment patterns
• Familiarity building internal AI tooling/SDKs/developer enablement frameworks
• Exposure to observability practices (logging, tracing, metrics) in application systems

Nice to have

• Streaming or ETL pipelines experience for ingesting structured and unstructured data
• BS required; MS/PhD preferred if experience demonstrates equivalent capability

Education

• BS in Computer Science/Engineering/Math or related field required (MS/PhD preferred)