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Retrieval Augmented Generation Rag Jobs in Indiana

Traction Ag, Inc.

Principal AI Systems Engineer

Auburn, IN · On-site +1

$170K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build a secure internal AI data and retrieval layer * Establish governance and safe AI usage ... generation, and cross-functional communication * Implementing RAG pipelines, vector search ...

Traction Ag Inc.

Principal AI Systems Engineer

Auburn, IN · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build a secure internal AI data and retrieval layer * Establish governance and safe AI usage ... generation, and cross-functional communication * Implementing RAG pipelines, vector search ...

Traction Ag Inc.

Principal AI Systems Engineer

Auburn, IN · On-site

$170K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build a secure internal AI data and retrieval layer * Establish governance and safe AI usage ... generation, and cross-functional communication * Implementing RAG pipelines, vector search ...

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Principal AI Systems Engineer

Traction Ag, Inc.

Auburn, IN • On-site, Remote

$170K - $190K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago

Job description

Traction Ag helps farmers simplify the business of farming through cloud-based software that brings together farm financials and operations.
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.
Core Priorities
  1. Build a secure internal AI data and retrieval layer
  2. Establish governance and safe AI usage patterns
  3. Ship high-leverage internal workflows and automations
  4. Enable responsible AI adoption across the company
  5. Create scalable foundations for future agentic systems

What the role is not:
  • An AI research role
  • A pure ML modeling role
  • A prompt engineering role
  • A people management role
  • A speculative innovation lab

What You Will Build
The Operating Layer
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

The Internal AI Workflow Platform
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

Operational Intelligence
  • 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

Security & Governance
  • 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

What We Are Looking For
Required
  • 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 TypeScript; 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.

Nice to Have
  • Familiarity with structured operating systems for scaling companies
  • Background in ag-tech, fintech, or B2B SaaS
  • Experience building internal developer platforms, plugin systems, or self-service tooling for non-engineers
  • Contributions to open-source AI tooling or a portfolio of internal tools you have built and shipped
  • Experience with our stack: Atlassian, Notion (including the API), HubSpot, Slack, Jira, Figma, Google Workspace, Canva

What Success Looks Like
Foundation
  • Initial secure AI retrieval architecture is operational against at least one core company data source
  • Foundational AI infrastructure, governance standards, and approved tooling patterns are established
  • At least two vetted internal AI workflows are published and actively used

Quick Wins - First 90 Days
  • Three to five automations are shipped and saving measurable time across multiple departments
  • At least one cross-functional AI workflow is operational and adopted by non-technical teams
  • A prioritized six-month roadmap for AI infrastructure, workflow automation, and governance is delivered to leadership

Organizational Trust
  • You have established strong working relationships across department leadership
  • The organization trusts the systems, guardrails, and architectural direction being established
  • The company has begun moving from fragmented AI experimentation toward secure, production-oriented AI adoption

What We Offer
  • Mission-driven work that directly supports farmers and rural communities.
  • A nimble, passionate team where your ideas have real impact.
  • Competitive and cost-effective benefits plans - Health, Dental, Vision, and Life Insurance
  • 401(k) Plans with Company Match
  • Unlimited Paid Time Off
  • Paid Holidays
  • A company culture rooted in our values:
    • Put the Farmer First
    • Gain Traction as a Team
    • Think Outside the Silo
    • Take the Right Next Step
    • Choose Joy

Apply