Embedded AI Engineer for Real-World Impact

Shermco Industries

Irving (TX)

On-site

USD 150,000 - 210,000

Full time

44 hours ago

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Benefits offered by this job

Growth dept

Ownership

Microsoft tooling

Visible impact

Job summary

Shermco Industries is seeking a Forward Deployed AI Engineer to embed with Shermco business units and prove AI value in real workflows. You will work with field operations, estimating, sales, finance, HR, and other functions to identify opportunities and deliver practical AI solutions using low-code, Copilot Studio, Power Platform, and Fabric.

You will ship working solutions, partner with the AI Product Engineer for complex needs, and measure adoption and business outcomes.

Qualifications

5+ years of experience in software engineering, data engineering, applied machine learning, solutions engineering, or a related technical role, including 2+ years building AI or LLM-based solutions used in production.
Strong Python and SQL skills, plus experience integrating with REST APIs and enterprise systems.
Hands-on experience building with LLMs, including prompt design, retrieval-augmented generation, tool use, and basic evaluation.
Experience with a cloud AI platform such as Azure AI Foundry, Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Demonstrated ability to run discovery with stakeholders from front-line staff to executive leadership and translate ambiguous problems into scoped, buildable solutions.
A track record of shipping quickly, measuring results, and iterating based on user feedback.
Clear written and verbal communication, including explaining AI capabilities, limits, and risks to non-technical audiences.
Comfort working independently, traveling to business unit locations (approximately 10%), and managing several engagements at once.

Responsibilities

Understand workflows across field operations and business units to identify AI opportunities.
Define scoped AI problems and size opportunities by time, cost, risk, or revenue impact.
Build solutions quickly using Copilot Studio, Azure AI Foundry, Fabric, and Power Platform.
Integrate with Salesforce, on-premises Business Central, Dayforce, and field service platforms.
Release to production with documentation and business ownership.
Hand off to AI Product Engineer for complex code needs.
Partner with Data & AI Governance Engineer to ensure data access and responsible AI standards.
Own adoption after launch through training and champions in the business unit.
Share knowledge and contribute to team standards.