Principal AI Systems Engineer

Traction Ag helps farmers simplify the business of farming through cloud-based software that brings together farm financials and operations. We’re hiring a Director of Marketing to lead and scale a modern B2B SaaS marketing engine focused on pipeline growth, brand positioning, and revenue impact.

In this role, you will operate as a cross-functional technical leader partnering closely with the COO and engineering leadership. You will help define the company’s AI architecture, tooling standards, and governance practices.

• An AI research role
• A pure ML modeling role
• A prompt engineering role
• A people management role
• A speculative innovation lab

Our internal AI operating layer. A secure internal AI layer that connects company knowledge systems and makes institutional context searchable, usable, and operational.

• Building AI-powered retrieval and synthesis workflows across Slack, CRM, Google, docs, project management, and meeting transcripts so teams can access institutional knowledge and historical context in seconds
• Creating scalable systems for meeting capture, decision logging, onboarding, SOP generation, and cross-functional communication
• Implementing RAG pipelines, vector search, embeddings, and AI orchestration frameworks that power the entire internal AI toolkit
• Reducing knowledge silos, duplicated work, and dependency on tribal knowledge by making information flow to where it is needed, when it is needed

A centralized library of reusable AI-powered workflows, automations, and internal tools employees can safely use without exposing sensitive company or customer data.

• Curated, tested AI workflows for each department that non-technical team members can invoke without prompt engineering from scratch
• Version control, access governance, and audit trails so the organization can scale AI usage without sacrificing security or consistency
• A framework that lets team members go from idea to prototype to production-ready workflow, with guardrails that keep outputs safe and on-brand

• Automations and agents that transform raw information into actionable insights, summaries, tasks, and operational reporting
• Tools that make operational metrics, goal tracking, and leadership reporting more accessible, more actionable, and harder to ignore
• Governance, security, and data quality standards for every internal AI system

• Define safe AI usage standards across the organization
• Establish data handling and model access policies aligned with security requirements
• Evaluate AI vendors, infrastructure, and deployment patterns for security and scalability
• Design human-in-the-loop workflows, auditability, and operational safeguards
• Ensure customer financial data is protected across all AI systems

• 7+ years in software engineering, data engineering, or platform/infrastructure roles, with at least 2 years focused on AI/ML systems or AI-powered tooling
• Demonstrated track record designing and implementing AI-powered retrieval systems, knowledge architectures, and workflow orchestration patterns in production environments.
• Proficiency in Python, Node, Angular, and Type Script; comfortable working across the stack from data pipelines to lightweight front-end interfaces
• Proven ability to build integrations across SaaS tools using APIs, webhooks, and automation platforms
• Strong understanding of context engineering: designing retrieval strategies, memory systems, and information architectures that make AI outputs reliable and high-quality
• Excellent communication: you can translate between technical architecture and business outcomes, and you can teach complex concepts to non-technical colleagues
• Comfortable operating autonomously, prioritizing ambiguous problems, and making pragmatic technical tradeoffs.

• Familiarity…