Forward Deployed Engineer

Instacart Instacart · Consumer · United States · Remote · Professional Services

Instacart's Enterprise Solutions team is seeking a Forward Deployed Engineer to embed within enterprise customer environments, build agentic AI solutions on top of their infrastructure, and collaborate with Instacart R&D to inform platform evolution. This role requires strong software engineering experience, hands-on LLM API usage, and customer-facing skills.

What you'd actually do

  1. Embed with enterprise retail customers and partners to understand their technical environments, data systems, and business workflows.
  2. Design, build, and deploy AI and agentic solutions tailored to each customer's specific infrastructure and needs, across Instacart's full platform suite.
  3. Extend, adapt, and integrate Instacart's core AI capabilities to fit customer ecosystems, even when those systems are undocumented or non-standard.
  4. Maintain a close working relationship with R&D: participate in product reviews, flag platform gaps encountered in the field, and propose concrete changes that would make the platform work better for enterprise customers.
  5. Collaborate closely with the AI Solutions Architect to translate domain requirements and architecture into working software.

Skills

Required

  • 5+ years of software engineering experience
  • Hands-on experience building with LLM APIs, function calling, tool use, agent frameworks, or RAG pipelines
  • Proficiency in Python or another scripting/backend language
  • Proven ability to integrate with messy, heterogeneous enterprise data environments
  • Direct experience with external enterprise customers or technical stakeholders
  • Strong working knowledge of retail and e-commerce system fundamentals
  • Strong communication skills

Nice to have

  • Prior work in a forward deployed, embedded engineering, or professional services capacity.
  • Background at a startup or early-stage company
  • Experience in enterprise software implementation, systems integration, or solutions engineering.
  • Exposure to retail tech, e-commerce, or supply chain systems.

What the JD emphasized

  • Hands-on experience building with LLM APIs, function calling, tool use, agent frameworks, or RAG pipelines—you have shipped something agentic that real users depended on.
  • Proven ability to integrate with messy, heterogeneous enterprise data environments — undocumented APIs, schema mismatches, auth complexity, and legacy systems that do not behave the way the docs claim.
  • Direct experience with external enterprise customers or technical stakeholders in a consulting or customer-facing capacity — earning trust in the room matters as much as writing code.

Other signals

  • building agentic AI solutions
  • embedding directly with enterprise retail and CPG partners
  • design, sell, and deliver AI-powered solutions at scale