Insight Global

GenAI Engineer

โญ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI Engineer, a 6-month contract to hire, fully remote (US residents only), with a pay rate of $50-100/hr USD. Requires 3-10+ years in Data Science, recent GenAI experience, and skills in Scala, AI, and ML.
๐ŸŒŽ - Country
United States
๐Ÿ’ฑ - Currency
$ USD
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๐Ÿ’ฐ - Day rate
800
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๐Ÿ—“๏ธ - Date
April 28, 2026
๐Ÿ•’ - Duration
More than 6 months
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๐Ÿ๏ธ - Location
Remote
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๐Ÿ“„ - Contract
W2 Contractor
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๐Ÿ”’ - Security
Unknown
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๐Ÿ“ - Location detailed
United States
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๐Ÿง  - Skills detailed
#ML (Machine Learning) #AI (Artificial Intelligence) #Consulting #Strategy #Data Science #Scala
Role description
โ€ข Title: GenAI Engineer โ€ข Location: Fully remote (must live in US) โ€ข Duration: 6 month contract to hire โ€ข Pay: 50-100/hr USD โ€ข W2 Only Job Description: An AI Consulting firm is looking for an GenAI Innovation Engineer/GenAI Forward Deployed Engineer for greenfield product development. They will be building industry-specific AI solutions (Healthcare, BFSI) from scratch. The goal is to create reusable frameworks that the company can coinvest in with pilot customers. This team is building a โ€œstart upโ€ within the company to be the GenAI brains. There will be a lot of brainstorming, prototyping, and fun conversations. They will also be joining customer meetings as the technical POC to help solve customersโ€™ problems. The day to day will be 60% Hands-on Engineering: Building production-grade AI/ML pipelines and reusable frameworks, 20% Research, 20% Architecture & Strategy: Designing for scalabilityโ€”turning a specific client solution into a reusable products. Must Haves: โ€ข 3-10+ years of experience within Data Science and more recent experience with GenAI โ€ข Ability to: Rapidly prototype and build agentic solutions, Co-develop code with client engineering teams, Translate abstract requirements into functional software, Integrate AI models into business workflows, Refine solutions based on real-time feedback, Rapid delivery of functional AI MVPs, High-value, scalable intellectual property assets, Validated technical feasibility of AI concepts, Client readiness for operational ownership.