Staff Software Engineer, AI

Stord

About The Position

Stord is revolutionizing the logistics industry with our cloud-based supply chain platform. Our AI team builds intelligent, LLM-driven features — including conversational agents, automated workflows, and AI-powered decision support — that are deeply integrated across Stord's product suite. We are seeking a Staff Software Engineer to serve as the technical lead of the AI Platform team. This is not a heads-down IC role — you will be the technical pillar of the team, owning architecture decisions, driving technical strategy, and raising the quality bar for everyone around you. You'll work hands-on in our TypeScript-based AI platform built on Cloudflare Workers while simultaneously multiplying the output and growth of the engineers on your team. The right person for this role has strong opinions, loosely held — informed by deep experience, not by pasting LLM output into a design doc. You have a track record of building and shipping agentic AI systems in production, and you know how to direct AI-assisted development toward high-quality outcomes rather than accepting whatever comes out of the model.

Requirements

TypeScript (3+ years in production) — You write idiomatic, well-structured TypeScript and are comfortable owning a large TypeScript codebase. This is the primary language of the AI platform.
Distributed Systems & Edge Computing — Experience designing stateful systems at the edge. Cloudflare Workers, Durable Objects, or similar edge runtime experience is strongly preferred.
AI/LLM Application Development — You have built and shipped agentic or LLM-powered features in production. You understand prompt engineering, tool/function calling, context management, and the practical challenges of making AI systems reliable.
Data Streaming Platforms — Experience consuming from or integrating with event streaming systems (Redpanda preferred, Kafka acceptable). Familiarity with Redpanda Connect or Kafka Connect for building data pipelines that feed AI features is a plus.
API Design & Integration — Experience designing and consuming RESTful APIs, OpenAPI specifications, and event-driven architectures. You'll integrate with multiple backend services daily.
Database & Persistence — Strong SQL fundamentals. Experience with embedded/edge databases (D1, SQLite) or PostgreSQL. Drizzle ORM experience is a plus.
Cloud Platforms — Hands-on experience with Cloudflare, GCP, or AWS. Understanding of serverless and edge deployment models.
Observability — Experience instrumenting production systems with OpenTelemetry, Datadog, or similar. You know what to measure and how to debug distributed systems in production.
Technical Authority — You form well-reasoned technical opinions based on experience and analysis, and you can defend them in a room of strong engineers. You don't outsource your judgment to an LLM.
Force Multiplier Mindset — You measure your impact by team output, not personal ticket velocity. You actively seek opportunities to unblock, teach, and elevate others.
Accountability & Presence — You show up for the team. You're in the design reviews, the release meetings, the architecture discussions. You own outcomes, not just code.
Communication & Influence — You can explain complex technical decisions to PMs, executives, and junior engineers alike. You build consensus through clarity, not authority.
Directed AI-Assisted Development — You know how to use AI coding tools as a force multiplier while maintaining quality. More importantly, you can teach a team to do the same — establishing practices that produce better results than unguided AI output.

Nice To Haves

Elixir/Phoenix experience or familiarity (downstream services use Elixir)
Experience with the Cloudflare developer platform (Workers, Durable Objects, Sandboxes, Containers, D1, R2, Vectorize, AI Gateway, Workflows, Queues)
Experience with Anthropic Claude, the AI SDK (ai / @ai-sdk/anthropic), or Model Context Protocol (MCP)
Knowledge of logistics, e-commerce, or supply chain domains
Contributions to open-source TypeScript or AI projects
Experience with WebSocket-based real-time systems
Familiarity with scope-based authorization and multi-tenant systems

Responsibilities

Technical Leadership & Strategy
Own the technical vision and architecture of Stord's AI platform, making decisive design choices and communicating the "why" to stakeholders at all levels
Drive technical strategy in partnership with the Sr Engineering Manager and Sr Product Manager, translating product goals into sound engineering plans
Evaluate build-vs-buy decisions, new tools, and architectural patterns with a pragmatic, production-first mindset
Establish and enforce technical quality standards through design reviews, code reviews, and architectural guidance
Show up — be present and accountable in critical ceremonies including design reviews, go/no-go releases, sprint planning, and cross-team syncs
Hands-On Engineering
Design and build core components of our AI platform: agent orchestration, tool systems, prompt management, and integration APIs
Work daily in our TypeScript stack: Hono on Cloudflare Workers, Durable Objects for stateful agents, D1/Drizzle for persistence, and the AI SDK (Anthropic Claude) for model interaction
Build robust, scope-aware tool systems that safely expose platform capabilities (orders, inventory, knowledge base) to AI agents
Design fault-tolerant integrations with downstream services, including Elixir/Phoenix APIs, and ensure graceful degradation
Integrate ML model outputs via API layers as the team's needs evolve, without requiring deep data science expertise
Team Multiplier
Be the engineer other engineers go to — cultivate trust and influence with senior and mid-level engineers through consistent technical excellence and availability
Mentor engineers at all levels, with particular emphasis on growing senior engineers into more autonomous technical decision-makers
Model and teach directed agentic development practices: how to use AI coding tools effectively, maintain a strong independent technical POV, and produce high-quality results rather than accepting raw model output uncritically
Create leverage through reusable abstractions, clear documentation of architectural decisions, and developer tooling that makes the rest of the team faster
Proactively identify technical risks and opportunities — don't wait to be assigned a ticket
Cross-Functional Collaboration
Partner with Product Management to shape the AI product roadmap, providing technical perspective on feasibility, sequencing, and trade-offs
Work with the Group Principal Engineer to align AI platform architecture with broader engineering strategy
Collaborate with Data Scientists and ML Engineers to understand model requirements and design clean integration boundaries
Support other product engineering teams in adopting AI capabilities within their domains