AI Engineer

🔥 1 minute ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Factorial

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2016

👥 HR Tech

☁️ SaaS

🤝 B2B

💰 $120M Debt financing on 2025-04

HR Tech • SaaS • B2B

Factorial is a provider of HR-focused software delivered as a web/cloud product that supports recruitment, onboarding and broader people-operation workflows. The available content emphasizes recruitment and onboarding workflows, job postings and international/remote hiring, and includes privacy/cookie notices consistent with a customer-facing SaaS application. Factorial appears to serve businesses (B2B) with a platform for managing HR processes and supporting distributed teams.

📋 Description

• Design, build, and maintain AI systems that turn customer conversations and uploaded documents into grounded, auditable cost estimates • Build and maintain LangGraph agents, including ReAct retrieval sub-agents, custom middleware, Pydantic-typed graph state, and streaming flows • Own retrieval quality end to end through collection routing, LLM-driven metadata filters, similarity thresholds, query rewriting, semantic chunking, and citation tracking • Integrate AWS Bedrock, OpenAI, and self-hosted vLLM behind an abstract interface • Develop and maintain API services, relational and domain-knowledge data stores, vector stores, and AI workflow observability/tracing • Set technical direction for the AI workstream • Review designs and code, mentor engineers, and align with product stakeholders • Deliver against the roadmap and improve agent success, retrieval accuracy, grounding, latency, and LLM cost-efficiency

🎯 Requirements

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or Mathematics • Minimum of 6 years of progressive software engineering experience • 1+ years building production LLM-powered or machine-learning systems, including agents, RAG, or prompt/evaluation pipelines • Proven delivery in a fast-paced environment • Availability to overlap U.S./Eastern-Time business hours for client meetings • Expert production software engineering and LLM-powered systems experience • Expertise in agents/orchestration, retrieval-augmented generation, and prompt/evaluation pipelines • Fluency using AI development tools • Deep understanding of retrieval and grounding, embeddings and vector search, multi-model integration, and cost/latency tuning • Working knowledge of the cost-estimation / Work Breakdown Structure domain, or ability to learn a deep domain quickly • Ability to analyze complex, non-deterministic AI behavior from production traces and deliver scalable, well-tested solutions • Exceptional communication of technical and model-behavior concepts to non-technical and client stakeholders • Confidence in live U.S./ET client meetings and disciplined asynchronous written communication across time zones • Proven ability to make critical, time-sensitive decisions with limited information • High ownership, motivation, bias to action, and willingness to go the extra mile

🏖️ Benefits

• Flexible ways of working • Long-term development opportunities • Collaboration, trust, and quality-focused work environment • Autonomy with accountability and influence over architecture, technical direction, and standards

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