Pareto AI

Pareto AI

Applied AI Engineer

US Remote

Sponsorship not specifiedDetected 105 days ago
TypeScriptPythonDistributed SystemsData StructuresAlgorithmsVector DatabasesAWSGCPTerraformTemporalData EngineeringLLMsRAGAI OrchestrationResearchCommunication

About the role

  • ABOUT PARETO Humanity is in a virtuous cycle: human insight improves AI, and better AI expands what people can do.
  • Sustaining it depends on the one input that can't be automated: expert human judgment https://pareto.ai/blog/debating-persuasive-llms-truthful-answers.
  • This RL environment and human-data infrastructure is already in production.

Responsibilities

  • Design and build the pipelines that generate synthetic tasks and evaluation environments for AI model training - this is the factory floor of AI development, producing training fuel for next-generation models, not the models themselves
  • Own and lead the most complex system design discussions - produce one-page technical scoping documents that surface hidden risks before development begins, define technology stacks, and establish engineering guidelines that let the team move fast without breaking things
  • Rapidly assess whether a technical idea is worth building - get early signal, align stakeholders, and kill or accelerate accordingly
  • Partner closely with research, operations, and data teams - juggle multiple workstreams, make smart tradeoff decisions as priorities shift, and translate ambiguous business needs into concrete technical architecture
  • Build reusable frameworks and engineering guidelines that raise the team's collective execution muscle
  • Production experience building and shipping agentic workflows, multi-agent orchestration, HITL pipelines, and LLM-powered applications with measurable business outcomes - RAG, vector stores, semantic search, and multi-model LLM stacks in production, not just demos
  • We work with leading frontier labs like Anthropic and GDM, and we give skilled people everywhere a way to shape the future of AI and share in what it creates.

Requirements

  • You may be a good fit if you have
  • 8+ years of software engineering experience with a track record of owning complex systems end-to-end
  • Experience with distributed systems architecture applied to AI or data platforms - reliable, observable, and scalable systems built in service of a product
  • Daily proficiency with agentic coding tools (Claude Code, Cursor, or equivalent) - you use these to multiply your output, not pad it

Nice to have

  • This is the dream background.
  • Familiarity with preference data and reward models used in AI model training (RLHF, RLVR, or similar)
  • Proficiency with our stack: Python, TypeScript, AWS, GCP, Terraform, Temporal Cloud, containerization, LLM gateways, RAG frameworks, and data pipeline tooling
  • Ability to employ data structures and algorithms when forming AI/LLM solutions
  • Ability to reason about requirements with a bias for Essentialism

Company info

  • At Pareto, we build the platform that turns that judgment into the data https://pareto.ai/blog/community-driven-knowledge-resource-ai, evals https://pareto.ai/blog/introducing-attunebench, and RL environments frontier models https://pareto.ai/blog/llm-metacognition-shared-and-shallow learn from.
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This listing is sourced directly from Pareto AI's careers page and normalized into a canonical job model.