Forward Deployed Engineer (AI COE)

Lineage Logistics•Detroit, MI

1d•Remote

About The Position

The Forward Deployed Engineer (FDE) is the primary delivery mechanism of Lineage’s enterprise AI Center of Excellence (CoE), the engineer who sits at the intersection of the AI platform and the business problem. FDEs embed directly with business functions across Lineage to translate high-value use cases into production AI solutions that make our employees more productive and our operations more effective. At Lineage, the aim is not to build the largest technology team; instead, we are creating a small, highly skilled group that focuses on having the right mix of talents, skills, and the capacity to learn in areas that define our core differentiation. We leverage cloud services, best-of-breed libraries and components, and external teams to augment our capabilities with sufficient capacity. This means that in addition to being a firsthand technologist, you also need to be able to take a project from an ambiguous business need to a production-grade solution, and to collaborate with internal and external partners to deliver. As a company, Lineage builds state-of-the-art systems to make our employees productive, to meet and exceed our customers’ expectations, to assist in our growth, and to create a technology platform that enables Lineage to achieve its vision of transforming the food supply chain. This is one of the most impactful roles in that journey, and it will require someone who has a true passion for solving real business problems with the responsible application of AI, and for raising the bar for the engineers who follow.

Requirements

University degree in computer science, software engineering, or a related field and/or > 10 years of relevant work experience.
4+ years of experience in software engineering, applied ML/AI, or solutions engineering, with direct client- or stakeholder-facing delivery.
Proficiency in Python and experience with modern AI/ML tooling (LLM APIs, agent frameworks, vector databases, RAG pipelines).
Demonstrated ability to take a project from an ambiguous business need to a production-grade solution with minimal oversight .
Experience working in fast-paced, early-stage, or consulting-style environments where scope and priorities shift frequently .
Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data infrastructure.
Demonstrate excellent verbal and written communication skills, including the ability to present to business leaders and translate technical concepts.
Manage stakeholder relationships and expectations across multiple engagements.
Possess a willingness to be coached and proactively seek feedback.
Manage multiple assignments / projects simultaneously.
Properly set priority and order for work.
Work in a fast-paced, agile environment.
Ask for help and provide it to others.
Understand your skills and your talents and apply them appropriately.
Learn and apply modern technologies and business concepts.
Mentor and provide guidance, especially to other technical resources.

Nice To Haves

Experience with enterprise AI platforms such as Claude Enterprise, OpenAI (ChatGPT Enterprise), or other similar tools is a plus.
Track record of shipping AI/ML use cases in enterprise environments (financial services, healthcare, manufacturing, logistics , or similar) is a plus.
Experience building with agentic AI frameworks (e.g., LangChain , CrewAI , AutoGen ) and evaluating model outputs systematically is a plus.
Previous exposure to supply chain technologies including WMS, TMS, YMS, and related systems is a plus.

Responsibilities

Embed with business stakeholders to deeply understand workflows, pain points, and opportunities for AI-driven improvement.
Scope, architect, and deliver end-to-end AI solutions, from data ingestion , prompt engineering , skill and agent build through deployment, monitoring, and iteration.
Leverage the CoE’s core AI platform, working closely with Platform Engineers to extend tooling and surface platform gaps.
Ship flagship use cases that establish repeatable delivery patterns for the broader team.
Collaborate with Business Analysts to quantify use-case value, prioritize the engagement pipeline, and measure post-deployment impact.
Partner with Solutions Architects and Data & Integration Engineers to ensure solutions integrate cleanly with enterprise systems and data sources.
Document solution architectures, runbooks, and lessons learned to accelerate future engagements and enable developer enablement across the enterprise.
Consistently deliver high-quality software and processes in usable increments.
Mentor and onboard new Forward Deployed Engineers as the team scales.
Grow and maintain a broad and deep knowledge of supply chain operations and the ways AI can be applied to them.