Senior Software Engineer, Applied AI

• Pay or shift range: $159,000 USD to $178,000 USD
  The estimated range is the budgeted amount for this position. Final offers are based on various factors, including skill set, experience, location, qualifications and other job-related reasons.

Flock Freight is looking for a Senior Software Engineer, Applied AI to help the company adopt AI in ways that produce measurable business impact. This is a hands‑on, internal forward‑deployed engineering role. You will embed with teams across the business, identify high‑value workflows, build AI‑powered agents, copilot experiences, and integrations, and help those solutions become part of how people work every day.

The mandate is broader than reducing time to insight. You will help Flockers use AI to make better decisions, complete work faster, and improve operational outcomes. That may include enabling self‑service access to data, embedding copilots into existing tools and workflows, automating repetitive operational work, or developing new agentic experiences where they can deliver meaningful ROI.

You will own problems from discovery through production, delivery, and adoption. You will work closely with Platform Ops and business teams to understand real workflows, prototype quickly with users, iterate from feedback, support rollout and enablement, and measure whether the solution creates durable value. The goal is not to ship isolated demos. It is to build trusted AI capabilities that teams use, that improve business performance, and that can be reused across Flock.

The secondary focus is contributing to Freight Factory automation as product roadmap priorities dictate. Both areas are product‑driven. This role has optionality by design, with a natural path into broader product engineering over time.

Team/Department Overview: Infrastructure Engineering, reporting to the Senior Director of Engineering, Infrastructure & Applied AI

• Embed with business and operational teams to understand their goals, workflows, pain points, and constraints, then identify where AI can produce meaningful and measurable impact.
• Translate ambiguous business problems into clear solution hypotheses, prototypes, production plans, and success measures.
• Build side by side with end users and Platform Ops, incorporating feedback quickly and driving solutions from initial discovery through production adoption.
• Own delivery end to end, including technical design, implementation, rollout, reliability, user feedback, and iteration.

• Design and build AI agents, copilot experiences, and intelligent automations using LLMs, RAG, tool calling, agentic frameworks, and enterprise AI platforms.
• Connect AI capabilities to enterprise data and systems, including Snowflake, operational databases, APIs, and internal platforms, with appropriate evaluation, observability, security, and feedback loops.
• Build experiences that help employees query data, make decisions, and take action conversationally inside the tools and workflows they already use.
• Contribute to Freight Factory automation as product roadmap priorities dictate.

• Partner with Platform Ops and business leaders to support workflow redesign, rollout, training, and change management so new capabilities become part of day‑to‑day operations.
• Act as a trusted technical partner to non‑technical teams, helping them understand what AI can do, where it is appropriate, and how to use it effectively and responsibly.
• Develop lightweight enablement materials, examples, and reusable playbooks that help teams adopt AI tools and identify additional high‑value opportunities.
• Create…