Lead AI Engineer (Brilliant Harvest)
About the Role
As a Lead AI Engineer, you will play a key individual contributor role in designing and delivering production-ready AI-powered applications for the Brilliant Harvest platform. Combining deep technical expertise with leadership skills, you will mentor teammates, guide architectural decisions, and ensure the delivery of scalable, high-quality software solutions. Working closely with the VP of AI Engineering and the AI Architect, you will help shape the technical direction of our AI stack — from RAG pipelines and agentic workflows to document ingestion and model integration.
This role is ideal for someone who thrives in a fast-paced environment, loves solving complex problems, and is excited about taking ideas from concept to deployment in a domain where AI is transforming a legacy industry.
Key Responsibilities
Architect & Build
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Design, develop, document, and maintain robust prototypes and scalable production systems, with a focus on applied AI/ML, RAG architectures, and agentic workflows.
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Build and improve document ingestion pipelines that form the knowledge foundation of the platform, ensuring data enrichment, accuracy, and compliance with manufacturer standards.
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Evaluate and integrate LLMs, agent frameworks, and supporting tooling as the frontier model landscape evolves, collaborating with the AI Architect on vendor and model selection.
Technical Leadership
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Participate in and often lead brainstorming sessions, design reviews, code reviews, and architecture evolution discussions, ensuring best practices and long-term technical sustainability.
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Champion coding standards, automated testing, CI/CD practices, and AI-first development workflows (e.g., Claude Code or similar agentic tools) to improve velocity and quality.
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Contribute to the analysis of business requirements, prepare design and implementation recommendations, and provide reliable development effort estimates.
Cross-Functional Collaboration
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Work collaboratively across Product, Data, Design, and QA teams to drive outcomes aligned with business objectives and the product roadmap.
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Review and provide feedback on the technical feasibility of UI/UX designs, ensuring seamless integration with backend systems and AI capabilities.
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Translate data requirements and AI capabilities into clear, actionable specifications, and communicate technical constraints and tradeoffs to non-technical stakeholders.
Mentorship & Team Development
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Provide hands-on guidance, mentorship, and knowledge sharing to junior and intermediate engineers, fostering a culture of learning and innovation — as an individual contributor working alongside them, not as their manager.
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Promote a "Systems Thinking" mindset, helping engineers move from writing code to orchestrating AI-generated solutions.
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Design workflows that use AI to accelerate the growth of junior talent rather than automating them out of the process.
Qualifications & Skills
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5+ years of professional software engineering or data science experience, with at least 2 years focused on AI/ML systems in production.
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Proven track record deploying generative AI, LLMs, RAG architectures, or document ingestion pipelines with data enrichment in a production environment.
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Strong proficiency in Python and at least one of: TypeScript, C# (.NET), or a modern backend language.
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Experience with React, React Native, or modern frontend frameworks and how they integrate with AI-powered backends.
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Solid understanding of microservices architecture, API design, and cloud infrastructure.
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Demonstrated ability to mentor junior engineers and influence technical direction without formal authority.
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Experience working in a startup environment is considered a strong asset.
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Experience with agentic workflows, prompt engineering best practices, and AI-first development tooling (e.g., Claude Code or similar) is a strong asset.
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Familiarity with the agriculture, heavy equipment, or