Senior AI Engineer

FutureFit AI

. Design, build, and ship LLM-based product experiences end to end .

Posted 10/9/2026full-timeRemote • New York • United States, CanadaSenior💰 $150,000 - $185,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping LLM-based products, with strong applied machine learning and AI engineering skills. Proficient in developing evaluation metrics, data governance, and integrating AI systems with enterprise workflows.

Highest-signal resume keywords

LLM-Based Product DevelopmentMachine Learning EngineeringPrompt EngineeringData GovernanceAPI Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning FundamentalsPredictive ModelingClassification ModelingPythonSQL

Soft Skills

Technical LeadershipCommunication to Non-Technical Audiences

Tools & Technologies

AWSSageMakerData PipelinesSaaS Platforms

Industry Keywords

Labor Market DataHuman-in-the-Loop ReviewEvaluation MetricsAgentic WorkflowsCase Management Systems

Tech Stack

Tools & technologies

AWSPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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