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GenAI Forward Deployed Engineer

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: Insight Global
Full Time position
Listed on 2026-09-08
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 140000 USD Yearly USD 100000.00 140000.00 YEAR
Job Description & How to Apply Below
  • 3+ years of experience within GenAI - ability to create multi-agent orchestration using Auto Gen, Lang Graph, CrewAI, OpenAI Agents SDK, and orchestration platforms like Azure AI Foundry Agent Service or AWS Bedrock Agent Core
  • Soft skills:

    adaptable, creative, determined, pragmatic, curious, external passion, entrepreneurial, scrappy, non-traditional thinker, positive temperament, comfortable wearing multiple hats, dreamer, emotional intelligence.
  • 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
Job Description

Insight Global is seeking multiple GenAI/Forward Deployed Engineers to join one of their top consulting clients. This client paves the way for AI first thinking; providing innovative AI solutions across multiple industries. We are seeking multiple GenAI engineers to join the “Incubator”, an AI first team focused on cutting edge client solutions as well as go-to-market products, leveraging things like multi-agent orchestration and rapid reusable prototyping.

This team is effectively building a “startup” within the organization to serve as the GenAI brain trust for the entire company.

The work will involve frequent client meetings, solving business problems with AI, brainstorming new AI capabilities to take to market, prototyping, and engaging in energizing technical conversations. Day to day responsibilities will include approximately 60% hands‑on engineering (building production‑grade AI/ML pipelines and reusable frameworks), 20% research, and 20% architecture and strategy—designing for scalability and transforming specific client solutions into reusable products.

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