Forward Deployed Engineer, AI Enablement

Your users are Stord employees — you get direct, immediate feedback on the impact of what you build

Greenfield scope: we are early in systematically automating internal workflows with AI, and you will define how it's done

High autonomy: observe a problem, propose a solution, ship it — with minimal bureaucratic drag

Your work compounds: reusable modules and patterns you build accelerate every automation that follows

AI investment is a company-level mandate — you will have organizational support and visibility

AI-powered tooling for Customer Experience teams — triaging issues, surfacing context, automating resolution workflows

Finance automation — reconciliation, exception handling, and reporting workflows that currently require manual effort

Ops and logistics tooling — dashboards, alerting, and intelligent interfaces that reduce the manual burden on warehouse and transportation teams

LLM-powered interfaces that let non-technical teams query, act on, and get answers from operational data without needing engineering support

Workflow Automation

End-to-end automation pipelines: observe workflow → prototype → validate with domain experts → harden → ship to production

Agentic systems with proper logging, retries, monitoring, and edge case handling — not scripts that break silently

Integrations with internal systems (OMS, WMS, TMS, Billing) via APIs and event streams

Reusable automation modules that accelerate future workflow projects across the organization

Developer Productivity Tooling

Internal AI-powered tools that reduce friction across the engineering development lifecycle

Lightweight APIs and integrations that connect the systems engineers rely on daily

Tooling that helps engineers at Stord write, review, and ship code faster using agentic workflows

Internal Data and Analytics Products

Automated reporting and alerting that replaces manual data pulling and analysis

Dashboards and data products that surface operational intelligence to the teams who need it

Self-serve data interfaces that reduce the back-and-forth between operational teams and engineering

Embed with a team, map the workflow end-to-end, identify the highest-leverage automation target

Ship small, validate with domain experts, iterate fast — production discipline from the very first commit

Collaborate with Product Engineering when automations touch core platform systems; operate independently everywhere else

Document and publish reusable patterns so the next engineer — or the next automation — goes faster

What We're Looking For

Required

TypeScript / Node.js (3+ years): Production backend experience. You reach for the right tool, and this is your primary one.

Agentic AI development: You have built AI agents that automate real workflows in production — not toys, not demos.

CLI-native workflow: Claude Code, Cursor, Codex, or equivalent is your primary development environment. This is a hard requirement.

LLM integration: Proven experience with OpenAI, Anthropic, or equivalent — tool use, structured outputs, prompt engineering, error handling.

API design & integration: You have built RESTful APIs from scratch and integrated with complex internal systems.

Observability: You instrument your agents in production — logging, tracing, monitoring, alerting. You know when things break before users do.

Database: Advanced SQL with PostgreSQL. You can model data and write queries that matter.

High agency: You identify the problem worth solving, propose the approach, and drive to done with minimal direction.

Production discipline: Fast iteration does not mean fragile systems. You build things that stay running.

Required Soft Skills

Ownership & Accountability — You own features end-to-end and take pride in what you ship. You follow through from design to production and don't drop things.

Strong Communication — You can explain technical decisions and trade-offs to engineers, PMs, and stakeholders. You ask good questions and listen well.

Collaborative Approach — You work well with others, give constructive code review feedback, and actively seek input from teammates.

Production Mindset — You prioritize reliability and user impact. You think about failure modes, monitoring, and operational concerns as part of your design process.

Learning Agility — You're comfortable with rapidly evolving AI/ML technologies and tools. You stay current without chasing hype.

Directed AI-Assisted Development — You know how to use AI coding tools as a productivity multiplier while maintaining quality and your own technical judgment.

Strongly Preferred

Experience automating workflows in operational or back-office contexts (finance, support, logistics, HR)

Familiarity with Stord's stack: Elixir/Phoenix, TypeScript, Kafka, GCP

Vector databases and semantic search for internal knowledge retrieval

Experience building internal developer tools or platforms

Python for scripting, data wrangling, or model integration

Stord is a cloud-based supply chain platform that enables brands to compete and grow through end-to-end logistics solutions. We process over $10B in commerce annually and operate across Order Management (OMS), Warehouse Management (WMS), Transportation Management (TMS), Consumer Experience, and Demand Planning. We are backed by leading investors and are rapidly scaling our engineering organization to match our ambitions.