Senior AI Engineer

🕒 October 9

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🗽 New York – Remote

🗽 New York – Remote

💵 $150k - $185k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 4%

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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FutureFit AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

💰 Seed Round on 2022-03

Artificial Intelligence • B2B • SaaS

FutureFit AI is a software development company that empowers workers with an AI-powered tool designed to serve as a GPS for career navigation. By partnering with Fortune 500 companies, governments, and workforce development organizations, FutureFit AI provides solutions that support career transitions, from upskilling and reskilling to job placement. Utilizing over 350 million global talent profiles and proprietary algorithms, the company offers personalized roadmaps for learning and career support, effectively harnessing data to optimize workforce development and planning.

📋 Description

• Design, build, and ship LLM-based product experiences end to end • Develop conversational coaching and agentic workflows that complete multi-step tasks • Build tool-use and orchestration layers • Create coaching and career-pathway products grounded in observed career transitions and causal evidence about wages and lifetime earnings • Establish what labor-market and intervention data can and cannot support • Build evaluation harnesses, offline and online quality measurement, regression tracking, and human-in-the-loop review • Develop predictive, classification, and ranking models when appropriate • Prepare, label, govern, and maintain AI data pipelines and knowledge sources • Connect AI systems safely to internal tools, databases, SaaS products, case management systems, and enterprise workflows • Implement authentication, guardrails, and failure handling • Partner with Engineering, Product, and the VP of Data & AI • Help shape AI prompting, evaluation, agent permissions, and technical patterns • Provide technical leadership while building new products

🎯 Requirements

• Roughly 5+ years of strong applied ML/AI engineering experience • Track record of shipping systems into real products used by real people • Production experience building and shipping LLM-based features • Experience with prompt engineering, agentic workflows, tool use, function calling, retrieval, and orchestration • Experience building evaluations, quality metrics, regression tracking, and human-in-the-loop review for LLM systems • Strong machine learning fundamentals and hands-on predictive or classification model experience • Fluency in Python and SQL • Experience with ingestion and transformation pipelines, labeling, knowledge sources, and data governance • Experience integrating APIs, databases, SaaS platforms, third-party data providers, and enterprise systems • Understanding of safety and guardrails in consequential domains • Ability to explain models, agent behavior, evaluation results, and tradeoffs to non-technical audiences • AWS and SageMaker experience is a bonus • Experience with jobs-and-skills, HR, labor market data, O*NET, or ESCO is a bonus • Case management, government systems, recommender systems, ranking, search, RAG, labor economics, program evaluation, publications, talks, blogs, or open-source experience is a bonus • Your Education section states that formal education is not the focus and does not require a credential

🏖️ Benefits

• Remote work across the US and Canada • Hybrid office access for candidates in Toronto and New York City • Quarterly off-site and team gathering travel opportunities • Reasonable accommodation for disability during application, interviews, and employment • Equal opportunity and inclusive workplace • Human-reviewed, equitable AI-supported hiring process

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