AI Forward Deployed Engineer

Shermco Industries, Inc.•Irving, TX

3d•$130,000 - $140,000•Hybrid

About The Position

Shermco is hiring a Forward Deployed AI Engineer to embed with internal business units and identify where AI can improve how work gets done. The role involves learning workflows across field operations, estimating, sales, finance, HR, and other functions, then building and deploying solutions that demonstrate measurable business value. This is a hands-on builder role: the engineer moves quickly from discovery to production, gathers user feedback, and iterates. Low-code and configuration solutions built with Copilot Studio, Power Platform, and Microsoft Fabric are owned through production; solutions requiring extensive custom code or complex agents are handed off to the AI Product Engineer. Success is measured by adoption and business outcomes. The position is part of the Data & AI team and reports to the Sr. Director, Data & AI. It works closely with the AI Product Engineer and colleagues in data engineering, analytics, and governance. Internal Shermco teams are the customers. The role is hybrid, based at the Dallas/Las Colinas office, with approximately 10% travel. Candidates must be legally authorized to work in the United States without current or future employer sponsorship; Shermco does not provide visa sponsorship for this position.

Requirements

At least 5 years of experience in software engineering, data engineering, applied machine learning, solutions engineering, or a related technical role.
At least 2 years of experience building AI- or LLM-based solutions used in production.
Strong Python and SQL skills.
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.
Ability to conduct stakeholder discovery, 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 the ability to explain AI capabilities, limitations, and risks to non-technical audiences.
Ability to work independently, travel to business-unit locations approximately 10% of the time, and manage several engagements at once.
Legal authorization to work in the United States without current or future employer sponsorship.

Nice To Haves

Experience in a forward deployed, solutions engineering, internal consulting, or embedded product role.
Experience with Copilot Studio, Microsoft Fabric, Power Platform, or Microsoft Foundry.
Experience with agent frameworks and protocols such as Microsoft Agent Framework, Semantic Kernel, LangGraph, or Model Context Protocol (MCP).
Practical experience using Claude, ChatGPT, GitHub Copilot, or comparable AI tools to accelerate development.
Experience with Salesforce, on-premises Business Central, Dayforce, or field service management platforms.
Experience with document intelligence, unstructured data, or speech and image use cases.
Light front-end or low-code app-building experience for prototypes.
Background in construction, electrical, field services, or another operations-heavy industry.
Microsoft certification such as AI-102 or AI-900.

Responsibilities

Work with stakeholders at all levels, from technicians and field crews through executives, to understand workflows, needs, and organizational initiatives.
Turn ambiguous requests into scoped, written problem statements; identify and size AI opportunities by potential effects on time, cost, risk, or revenue; and recommend when AI is not appropriate.
Build trusted relationships with business leaders and front-line users so problems are surfaced early.
Build solutions using Copilot Studio, Azure AI Foundry, Microsoft Fabric, Power Platform, Claude, Python, and other approved AI tools and models.
Integrate solutions with operational systems such as Salesforce, on-premises Business Central, Dayforce, and field service platforms.
Put solutions in front of users early, gather feedback, and iterate toward measurable outcomes.
Agree on success measures with business owners before building, track post-launch results, and recommend changing course or stopping work that does not deliver value.
Take low-code and configuration solutions built on Copilot Studio, Power Platform, and Fabric through production, with a named business owner, documentation, and evaluation cases; support production solutions, including a light shared support rotation for business-critical solutions.
Hand off solutions requiring extensive custom code or complex agents to the AI Product Engineer, with documentation, known limitations, and data and access requirements.
Partner with the Data & AI Governance Engineer to ensure solutions follow data access, security, and responsible AI standards.
Drive adoption after launch through training, office hours, business-unit champions, and usage follow-up.
Teach business users to identify appropriate AI use cases and use approved AI tools effectively and safely.
Bring field insights to the Data & AI team to shape its roadmap, reusable components, and priorities.
Use AI-assisted development while remaining accountable for accuracy, security, and maintainability.
Contribute reusable patterns, prompts, templates, and lessons learned to team standards; share knowledge, provide peer review, and help shape Shermco's broader AI strategy.