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Salary: USD 203,745 - 275,655 / annual
Afresh is an AI platform for grocery retail, helping enterprise grocers like Albertsons, Meijer, and Wakefern optimize decisions across their operations. The company has achieved 70% revenue growth in 2025, scaled to 6 enterprise solutions live in over 10% of the U.S. grocery market, and prevented over 200 million pounds of food waste last year.
You will build and lead the forward deployed engineering team from the ground up. This team embeds with enterprise grocery customers, integrating into their data systems, deploying AI solutions on top of their infrastructure, and hardening successful patterns back into the platform.
As a player-coach manager, you will balance hands-on technical leadership with team development. You'll review architecture, unblock engineers, and code when needed, but most of your time goes to leading team execution and managing customer stakeholder relationships. You'll own the technical relationship with each customer's engineering and data leadership, setting delivery roadmaps and defending the architecture behind them. You'll partner with Deployment Strategists who own the commercial relationship, while you own the technical plan and execution.
Key responsibilities include: hiring and developing forward deployed engineers; leading execution across concurrent customer engagements; staffing engagements to balance customer needs, team growth, and platform development; running 1:1s and investing in career growth; reviewing architectures and code; owning one reference architecture for AI deployments across customers; deciding what gets hardened into the shared platform versus built for single customers; setting production standards for reliability, security, data residency, and AI system evaluation; partnering with platform engineers to turn field learnings into product; building repeatable playbooks and starter repos; and traveling to customer sites 25–40% of the time, weighted toward engagement kickoffs and readouts.
You'll work out how customers actually operate when processes are undocumented, translating broad business goals (like reducing shrink) into scoped programs with sequences, costs, and dates. You'll move fluidly between roadmap conversations with customer VPs and debugging sessions with your own engineers.
REQUIREMENTS:
- 10+ years in software engineering, solutions architecture, consulting, or technical customer-facing roles, including 2+ years managing engineers in services, post-sales, or forward deployed organizations
- Experience building a team from 0 to 1: hiring, setting standards, defining what good looks like
- Executive presence and ability to move between strategic and tactical conversations
- Architect's range across ingestion, data modeling, application, and AI; judgment to see how pieces fit and where risk sits
- Real data fluency: can assess unfamiliar enterprise data models within a day, plan around dirty data, fluent in SQL and modern cloud data platforms (Databricks, BigQuery, Snowflake)
- Track record of understanding how businesses actually run when undocumented
- Production AI and LLM experience across retrieval, tool use, and agentic workflows; habit of measuring quality
- Experience delivering inside enterprise environments (customer cloud, security reviews, change management, politics)
- Willingness to travel 25–40% to customer sites
NICE TO HAVE:
- Grocery, retail, or supply chain data experience
- Built a forward deployed, professional services, or solutions engineering function from scratch
- Knowledge graphs, ontologies, or semantic layers in production
- Experience delivering the same product both vendor-hosted and in customer cloud with ownership of abstraction layer
