Motion Recruitment Partners, LLC
Founding Engineer
Motion Recruitment Partners, LLC, San Francisco, California, United States, 94199
Founding Engineer – AI Startup (San Francisco, In‑Office)
An early‑stage, venture‑backed AI startup in San Francisco is hiring its first
Founding Engineer . This is a ground‑floor opportunity to shape the technical direction, build core systems from scratch, and influence product, culture, and engineering best practices. If you thrive in high‑ownership environments and want to help define the future of an emerging AI product, this role offers significant impact and autonomy.
What You’ll Do
Architect, build, and deploy end‑to‑end features across the stack—from backend services to intuitive user interfaces.
Design scalable, high‑performance APIs and microservices to support AI‑driven workloads.
Implement and maintain frontend applications with clean, responsive, and component‑driven UI architecture.
Collaborate closely with founders on product direction, technical strategy, and roadmap prioritization.
Integrate and optimize AI/ML models into production systems (LLMs, embeddings, inference pipelines, etc.).
Establish early engineering best practices around code quality, testing, CI/CD, observability, and security.
Own the full lifecycle of features from concept → architecture → implementation → deployment → iteration.
Help recruit and mentor the early technical team as the company grows.
Work in a fast‑paced, experimental environment where speed, ownership, and adaptability matter.
Tech Stack (Flexible, Not Required to Know All)
Frontend:
TypeScript, React, Next.js, Tailwind, Vite
Backend:
Node.js / TypeScript, Python, Go (optional), Postgres, Redis, GraphQL or REST
AI / ML:
Experience with LLM APIs, model fine‑tuning, vector databases (Pinecone, Weaviate, pgvector), embeddings, inference optimization
Infrastructure:
AWS or Google Cloud Platform, Docker, Kubernetes (nice to have), Terraform, serverless architectures
Tools & Systems:
GitHub Actions, CI/CD pipelines, monitoring/observability tools (Datadog, OpenTelemetry, Sentry)
You Might Be a Fit If You…
Have 4‑10 years of full‑stack engineering experience
Have experience (or strong interest) working with AI/LLM‑powered products
Are excited by ambiguity and comfortable owning 0?1 technical decisions
Enjoy rapid iteration and hands‑on prototyping
Value craftsmanship but know when to optimize for speed vs. long‑term maintainability
Want meaningful equity and the opportunity to shape product and culture from day one
Are able and excited to work
fully on‑site
in San Francisco
#J-18808-Ljbffr
Founding Engineer . This is a ground‑floor opportunity to shape the technical direction, build core systems from scratch, and influence product, culture, and engineering best practices. If you thrive in high‑ownership environments and want to help define the future of an emerging AI product, this role offers significant impact and autonomy.
What You’ll Do
Architect, build, and deploy end‑to‑end features across the stack—from backend services to intuitive user interfaces.
Design scalable, high‑performance APIs and microservices to support AI‑driven workloads.
Implement and maintain frontend applications with clean, responsive, and component‑driven UI architecture.
Collaborate closely with founders on product direction, technical strategy, and roadmap prioritization.
Integrate and optimize AI/ML models into production systems (LLMs, embeddings, inference pipelines, etc.).
Establish early engineering best practices around code quality, testing, CI/CD, observability, and security.
Own the full lifecycle of features from concept → architecture → implementation → deployment → iteration.
Help recruit and mentor the early technical team as the company grows.
Work in a fast‑paced, experimental environment where speed, ownership, and adaptability matter.
Tech Stack (Flexible, Not Required to Know All)
Frontend:
TypeScript, React, Next.js, Tailwind, Vite
Backend:
Node.js / TypeScript, Python, Go (optional), Postgres, Redis, GraphQL or REST
AI / ML:
Experience with LLM APIs, model fine‑tuning, vector databases (Pinecone, Weaviate, pgvector), embeddings, inference optimization
Infrastructure:
AWS or Google Cloud Platform, Docker, Kubernetes (nice to have), Terraform, serverless architectures
Tools & Systems:
GitHub Actions, CI/CD pipelines, monitoring/observability tools (Datadog, OpenTelemetry, Sentry)
You Might Be a Fit If You…
Have 4‑10 years of full‑stack engineering experience
Have experience (or strong interest) working with AI/LLM‑powered products
Are excited by ambiguity and comfortable owning 0?1 technical decisions
Enjoy rapid iteration and hands‑on prototyping
Value craftsmanship but know when to optimize for speed vs. long‑term maintainability
Want meaningful equity and the opportunity to shape product and culture from day one
Are able and excited to work
fully on‑site
in San Francisco
#J-18808-Ljbffr