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Senior Software Engineer (AI | Python | $350k + Equity)

Paradigm Talent3 months ago
San Francisco, CA, United States
On-site
Full-time
Junior Level (1-3 years)
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Job Description

Position Overview

Role: Senior Software Engineer — AI Infrastructure & Product

Location:

Onsite SF
Compensation: Up to $350,000 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 – moving quickly, shipping often, and expecting high ownership from every engineer. You’ll join as an early engineer and help shape the core platform that powers the product roadmap.

Key Responsibilities

  • 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.

Required Qualifications

  • 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 – designing systems that make customers and colleagues more effective.
  • High agency and ownership: pushing projects forward and taking responsibility for outcomes.

Preferred Qualifications

  • 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).

Benefits & Perks

  • Be part of a compact, technical team solving hard infrastructure problems at product speed.
  • Ownership and fast iteration cycles with the opportunity to build systems that directly enable product impact.
  • High-performing and pragmatic environment that values reliable shipping and continuous learning.
  • Exposure to cutting-edge AI infrastructure and product development.

Required Skills

AI Infrastructure
Model Inference
Python
Distributed Systems
Backend Engineering