Software Engineer (AI | Python | $250k + Equity)

Role: Software Engineer — AI Infrastructure & Product

Location: Onsite SF

Compensation: Up to $250,000 plus equity

We’re partnering with a fast-moving AI company building foundational infrastructure for ambitious, production-grade generative systems. The team is small, technical, and intensely product-focused, they move quickly, ship often, and expect high ownership from every engineer. You’ll join as an early engineer and help shape the core platform that powers the product roadmap.

What you’ll do

Ship production-grade systems from day one and own the services you build.

Design, implement and operate large-scale model serving and inference infrastructure.

Build robust indexing, retrieval and orchestration pipelines that support high-throughput workflows.

Own core product integrations: authentication, billing, and backend services that customer-facing apps depend on.

Improve observability, deployment automation, and reliability for critical systems.

Partner closely with product and research teams to translate experimental models into reliable features.

Contribute to hiring and help define engineering practices as the team scales.

You should have

3+ years building production backends or infrastructure for AI/ML products.

Strong engineering fundamentals in Python (or similar), with experience shipping scalable services.

Hands-on experience deploying and operating model inference or similar high-CPU/GPU workloads.

Familiarity with distributed queues, async job orchestration, and large asset pipelines.

A product mindset — you design systems that make customers and colleagues more effective.

High agency and ownership: you push projects forward and take responsibility for outcomes.

Nice-to-haves

Experience with retrieval/indexing approaches and integrating models into product flows.

Background in containerization, orchestration, and cloud infrastructure.

Prior experience at an early-stage, high-velocity startup or as an early technical hire.

Any applied ML or research experience (practical engineering is valued over academic credentials).

Why join

You’ll be part of a compact, technical team solving hard infrastructure problems at product speed. Expect real ownership, fast iteration cycles, and the opportunity to build systems that directly enable product impact. The environment is high performing and deeply pragmatic if you thrive on shipping reliably and learning quickly, you’ll fit right in.