Senior Software Engineer, Applied AI
About The Position
Flock Freight is seeking a hands-on, internal forward-deployed engineer to help teams across the company adopt AI in ways that create measurable business impact. The role involves identifying high-value workflows and building AI-powered agents, copilot experiences, and integrations that become part of employees’ everyday work. Solutions may enable self-service access to data, embed copilots in existing workflows, automate repetitive operational tasks, or introduce agentic experiences where they provide meaningful return on investment. The engineer owns problems from discovery through production, rollout, adoption, and measurement. They work closely with Platform Ops and business teams to understand workflows, prototype with users, incorporate feedback, support enablement, and assess durable business value. A secondary focus is contributing to Freight Factory automation as product roadmap priorities dictate. The position is product-driven and offers a potential path into broader product engineering. The role is in Infrastructure Engineering and reports to the Senior Director of Engineering, Infrastructure & Applied AI. Flock Freight targets candidates local to or willing to relocate to its San Diego headquarters, and is currently targeting talent in the San Diego/Encinitas and Chicago areas. The work uses a hybrid model with scheduled in-office and work-from-home days.
Requirements
- 3 to 5+ years of software engineering experience, including at least 1 year delivering applied AI, ML, or intelligent automation in production.
- Hands-on experience with LLMs such as OpenAI, Anthropic, Gemini, or similar, including prompt engineering, RAG, function and tool calling, evaluations, and agentic patterns.
- Strong software engineering fundamentals, including system design, and demonstrated ability to ship reliable production applications at high velocity.
- Strong proficiency in Python.
- Experience with APIs, data pipelines, integrations, and cloud-based application architectures.
- Experience with Git and GitHub workflows, CI/CD, observability, and modern development practices.
- Ability to work effectively with technical and non-technical partners across workflow discovery, coding, rollout, and measurement.
- Clear communication skills and ability to translate between business needs, user experience, and technical architecture.
- Comfort with autonomy, ambiguity, iterative delivery, and operationally focused work.
Nice To Haves
- Experience embedding with customers or internal business teams to discover workflows and deliver solutions in ambiguous problem spaces.
- Experience driving adoption of technical capabilities, including rollout, user enablement, feedback collection, and impact measurement.
- Experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, or similar, or workflow orchestration tools.
- Familiarity with enterprise AI platforms such as OpenClaw, Glean, Claude Cowork, or similar copilot-style tools.
- Experience with agentic process automation or RPA platforms such as Sola.
- Experience in logistics, freight, or other operations-heavy industries.
Responsibilities
- Embed with business and operational teams to understand goals, workflows, pain points, and constraints, and identify opportunities for measurable AI impact.
- Translate ambiguous business problems into solution hypotheses, prototypes, production plans, and success measures.
- Build alongside end users and Platform Ops, incorporating feedback and taking solutions from discovery through production adoption.
- Own end-to-end delivery, 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 conversational experiences that help employees query data, make decisions, and take action within their existing tools and workflows.
- Contribute to Freight Factory automation as product roadmap priorities dictate.
- Partner with Platform Ops and business leaders on workflow redesign, rollout, training, and change management.
- Advise non-technical teams on AI capabilities, appropriate use, and responsible use.
- Develop enablement materials, examples, and reusable playbooks to support adoption and identify further opportunities.
- Create user feedback channels and improve solutions based on behavior, adoption barriers, and business outcomes.
- Define success measures before building and instrument solutions to track adoption and business impact.
- Use impact and adoption data to decide whether to iterate, scale, or stop initiatives.
- Create reusable integration patterns, components, evaluations, and delivery playbooks to make future AI solutions faster and safer to deploy.
- Codify and share lessons across Engineering, Platform Ops, and the broader business.
- Help define the technical roadmap for applied AI within corporate systems.
Benefits
- Equity package for full-time employees.
- 401(k).
- Medical insurance, with HMO and PPO options and coverage for employees and dependents.
- Dental insurance, with coverage for employees and dependents.
- Vision insurance, with coverage for employees and dependents.
- Hybrid work model with scheduled in-office and work-from-home days.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
