Forward Deployed Engineer, AI Enablement

Stord is a cloud-based supply chain platform that enables brands to compete and grow through end-to-end logistics solutions. As a Senior Forward Deployed Engineer on the AI Enablement team, you will build AI systems that automate internal workflows, enhancing operational efficiency across various teams. This role emphasizes high autonomy and direct impact on the company's operations through innovative tooling and automation.

Responsibilities:

• Build tools for Internal Teams (CX, Finance, Ops, Logistics)
• Develop AI-powered tooling for Customer Experience teams — triaging issues, surfacing context, automating resolution workflows
• Automate finance processes — reconciliation, exception handling, and reporting workflows that currently require manual effort
• Create ops and logistics tooling — dashboards, alerting, and intelligent interfaces that reduce the manual burden on warehouse and transportation teams
• Implement LLM-powered interfaces that let non-technical teams query, act on, and get answers from operational data without needing engineering support
• Create end-to-end automation pipelines: observe workflow → prototype → validate with domain experts → harden → ship to production
• Design agentic systems with proper logging, retries, monitoring, and edge case handling — not scripts that break silently
• Integrate with internal systems (OMS, WMS, TMS, Billing) via APIs and event streams
• Build reusable automation modules that accelerate future workflow projects across the organization
• Develop internal AI-powered tools that reduce friction across the engineering development lifecycle
• Create lightweight APIs and integrations that connect the systems engineers rely on daily
• Build tooling that helps engineers at Stord write, review, and ship code faster using agentic workflows
• Automate reporting and alerting that replaces manual data pulling and analysis
• Create dashboards and data products that surface operational intelligence to the teams who need it
• Build 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

Requirements:

• 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
• 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
• 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