Forward Deployed Engineer

Harvest Group•Rogers, AR

About The Position

The Forward Deployed Engineer rethinks how Harvest Group’s Client Services work gets done by using AI to amplify the expertise and experience of the people doing the work. The role works alongside account managers, analysts, and client leads to understand existing workflows and redesign them with AI in mind. Focusing initially on one or two high-value processes, the engineer identifies friction, gaps, and manual effort; collaborates with process owners to create better workflows; and builds and ships the systems behind them, from quick automations to LLM-powered and agentic workflows. The role owns adoption, helping teams take up new tools and ways of working through training, enablement, and hands-on support. The Forward Deployed Engineer partners closely with Client Services leadership and Product and Technology teammates, and helps develop repeatable approaches for future Forward Deployed Engineers. This role must be based in Rogers, Arkansas. Harvest Group does not cover relocation for applicants who do not currently reside in Northwest Arkansas.

Requirements

At least 7 years of experience building and shipping software in product, solutions engineering, internal tooling, or similar business-problem-focused roles.
Hands-on experience shipping LLM-based solutions people rely on, including prompt and system design, retrieval over structured and unstructured data, agentic workflows, and output-quality evaluation.
Full-stack ability to build working solutions end to end.
Fluency with AI-assisted development tools as a core part of the development process.
Experience leading discovery with business teams by interviewing users, observing work, mapping processes, and facilitating sessions to design improvements or new workflows.
A track record of taking solutions from prototype to everyday use, with attention to reliability, cost, maintainability, and adoption.
Sound judgment about where AI creates value and the ability to make the case for what to build, change, or stop.
Ability to work effectively without direct authority and influence business leaders and engineers through sound thinking and follow-through.
Strong written and verbal communication skills with business and technical audiences.
Work samples to discuss during the interview, such as shipped solutions, redesigned processes, or case studies with measurable results.

Nice To Haves

Experience in a forward-deployed, solutions engineering, or embedded engineering role.
Background in agencies, consulting, or other client-services businesses.
Familiarity with retail, CPG, e-commerce, retail media, digital shelf, or similar integrated commerce domains.
Experience with MCP, agent frameworks, evaluation tooling, or workflow automation platforms.
Experience with Microsoft Azure and modern cloud data warehouses such as Snowflake, Databricks, or BigQuery.
Experience working near production systems, including APIs, source control, CI/CD, and observability.
Experience with React, TypeScript, .NET/C#, Python, and SQL.

Responsibilities

Embed with Client Services teams to understand their work, tools, and pain points, including undocumented processes.
Map current-state processes so the teams who own them can review, challenge, and improve them.
Partner with Client Services leaders and end users to design AI-first future-state workflows focused on outcomes such as time returned, faster turnaround, fewer errors, and fewer handoffs.
Build and ship AI-enabled solutions on Harvest Group’s platforms, including LLM-powered and agentic workflows, integrations, and data pipelines, moving from proof of concept to everyday use.
Partner with Technology teammates to harden, deploy, and support production solutions in accordance with Harvest Group’s architecture and security standards.
Make sound decisions about where AI fits, including build-versus-buy, model and tool selection, human review, cost, and reliability.
Handle client data responsibly and design appropriate privacy, security, and AI-output quality checks.
Drive adoption through training, enablement, and hands-on rollout support, staying with teams until new ways of working take hold.
Create technical and process documentation so solutions can be maintained, reused, and extended.
Define and track engagement success measures and communicate results to leadership.
Turn successful approaches into repeatable discovery and deployment methods and reusable components.
Share field learnings with Product and Technology leadership to inform platform and product direction.