Job Title: Founding Product Engineer (Full Stack)

Company Name: WindShift Labs

Job Url: https://wellfound.com/jobs/3901096-founding-product-engineer-full-stack-ai-platform

Job Description: WindShift Labs
WindShift builds the AI operating system for investment diligence, turning raw deal data into decisi
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Founding Product Engineer (Full Stack) -- AI Platform
$150k – $230k • 0.5% – 1.5%
|
Remote (
Canada
+1
)
 • 
Boston
|5 years of exp
|Full Time
Posted: today• Recruiter recently active
Job Location
Boston
Remote Work Policy
Onsite or remote

Hires remotely in
Canada - 
United States
Visa Sponsorship
Not Available

Preferred Timezones
Pacific Time, Mountain Time, Central Time, Eastern Time, Atlantic Time
Collaboration Hours
10:00 AM - 5:30 PM Eastern Time
Relocation
Allowed
Skills
Python
Distributed Systems
Redis
PostgreSQL
TypeScript
Product Design
Docker
React.js
AWS
Terraform
Next.Js
FastAPI
Langgraph
RAGs, ChatGPT, Hugging Face, LangChain, LlamaIndex, Transformers, VectorDB
Vector Databases (Pinecone Serverless, Qdrant, FAISS, ChromaDB)
About the job
Founding Product Engineer — AI-First Systems Architect
The Mission
WindShift is building the Operating System for AI-Native Investment Diligence.

We are redesigning execution around AI as a core primitive — not layering it onto legacy workflows.

The platform is live with paying customers. The architecture exists. We are scaling the AI-native execution layer into a durable enterprise system.

We are hiring a founding engineer who builds systems the AI-first way.

This role will help define the execution architecture that underpins a venture-scale AI-native platform.

What AI-First Means Here
We do not want manual feature builders.

We want engineers who:

Design systems where LLMs are orchestration primitives
Structure execution as agent graphs, toolchains, and evaluators
Treat Claude/Codex as collaborators, not autocomplete
Optimize for system leverage, not lines of code
Build evaluation loops, regression harnesses, and hallucination detection
Think in terms of compounding structured intelligence
If your default mode is writing everything manually before asking whether AI should orchestrate it, this role is not a fit.

What You’ll Architect
AI-Native Execution Layer
Multi-step agent pipelines (planning → retrieval → synthesis → verification)
Tool and adapter abstractions that allow structured orchestration
Canonical intermediate representations decoupled from rendering
AI-Driven Development Workflow
Structured prompting systems
Internal orchestration layers around Claude/Codex
Automated evaluation and regression testing
Cost-aware model routing and caching strategies
Production-Grade Infrastructure
Async worker reliability (retries, idempotency, backpressure)
Observability and traceability across agent runs
Multi-store data architecture (Postgres, Redis, vector DB, graph DB)
Terraform-managed AWS deployment (ECS, RDS, ALB)
The Standard
You should:

Have 5+ years shipping production systems
Be fluent in modern LLM tooling and orchestration frameworks
Understand distributed systems tradeoffs
Be comfortable designing architecture, not just implementing tickets
Operate independently in a high-context environment
You should not need step-by-step specs.

Why This Is a Rare Opportunity
AI-native execution will reshape professional services economics.

WindShift already compresses repeatable workstreams by 20–30% in live environments. The next phase is scaling that leverage structurally to >50%.

With a small, high-talent team, AI-first engineering is the multiplier.

This role is foundational to that leverage.