Afresh

Afresh

Lead Solutions Engineer, Integrations

Remote - United States · Full-time

Sponsorship not specified$134k-$181kDetected 2 days ago
SQLMachine LearningData EngineeringData ScienceExcelCustomer SuccessAR/VRResearch

About the role

  • Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
  • By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.

Responsibilities

  • A typical day might involve discussing data architecture with engineers, digging into customer data, and developing technical implementation strategies and specifications. Specifically, you will:
  • Own and execute integration projects from customer discovery through go-live - creating detailed project plans with milestones, risk mitigation, and success criteria, and coordinating internal and customer-facing stakeholders through each phase
  • flag misalignments and propose adjustments to design for the customer's approach
  • Analyze complex data relationships, identify root causes of mismatches or anomalies, and build custom queries or lightweight tools to streamline validation and data mapping work
  • Collaborate with data engineering, product engineering, and data science to drive integration delivery
  • Demonstrated ability to independently own and execute complex integration projects end-to-end, including scoping, stakeholder coordination, and on-time delivery

Requirements

  • Apply deep knowledge of Afresh's core data model and integration patterns to evaluate whether customer needs can be met through standard approaches
  • Strong attention to detail and ability to communicate clearly across technical and non-technical audiences
  • Proficiency in SQL, Excel, and other analytical tools
  • You have experience managing customer relationships and leading technical projects in fast-paced environments.
  • You are excited to reduce fresh food waste in the grocery industry, and help the planet in the process!

Nice to have

  • Experience with AI/ML systems and identifying issues with data inputs used in predictive analysis
  • This position is not eligible for company sponsorship.
  • Why You'll Love Working at Afresh
  • Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology.
  • Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore's Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
  • Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.

Compensation

  • Salary Range in U.S.: $134,000 - $181,000 + meaningful early stage equity & benefits

Benefits

  • Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh.
  • We also provide dedicated mental health support and counseling services.
  • Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
  • Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
  • Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
  • Full-time U.S. employees are eligible for these benefits

Company info

  • We believe in continuous learning.
  • Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.

Visa & Work Authorization

  • This position is not eligible for company sponsorship.

This listing is sourced directly from Afresh's careers page and normalized into a canonical job model.