Platform Engineer (LLM Infrastructure & Backend Systems)

Platform Engineer (LLM Infrastructure & Backend Systems) Inflection AI full-time mid Expired Job Description At Inflection AI, our public benefit mission is to harness the power of AI to improve human well-being and productivity. The next era of AI will be defined by agents we trust to act on our behalf. We’re pioneering this future with human-centered AI models that unite emotional intelligence (EQ) and raw intelligence (IQ)—transforming interactions from transactional to relational, to create enduring value for individuals and enterprises alike. Our work comes to life in two ways today: Pi, your personal AI, designed to be a kind and supportive companion that elevates everyday life with practical assistance and perspectives. Platform — large-language models (LLMs) and APIs that enable builders, agents, and enterprises to bring Pi-class emotional intelligence into experiences where empathy and human understanding matter most. We are building toward a future of AI agents that earn trust, deepen understanding, and create aligned, long-term value for all. About the Role We are seeking a Platform Engineer to join our team building backend infrastructure for new ML-powered enterprise products. This role is a unique opportunity to work at the intersection of backend engineering and machine learning systems, focusing on inference orchestration, model integration, and real-time deployment. The ideal candidate will have experience with backend development, production ML systems, and tools that scale enterprise-level applications. This is a good role for you if you: -Backend engineering experience with Python, TypeScript, or Node.js. -Hands-on experience working with production PyTorch models, model checkpoints, and inference logic. -Strong knowledge of building APIs and services that are scalable, stable, and secure. -Passion for bridging backend engineering and ML systems, especially at the infrastructure layer. -Familiarity with tools such as FastAPI, Postgres, Redis, Kubernetes, and React. -Desire to be hands-on and contribute to shaping the foundation of a new enterprise ML product. Responsibilities include: -Build and maintain backend services to support LLM integration, inference orchestration, and data flow. -Write clean, reliable Python code for experimentation, model integration, and production systems. -Collaborate closely with ML researchers to rapidly iterate on product ideas and deploy features. -Design and implement infrastructure to handle scalable inference workloads and enterprise-level use cases. -Own system components and ensure reliability, observability, and maintainability from day one. Employee Pay Disclosures At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary will fall in the range of approximately $175,000 - $350,000 depending on experience. This estimate can vary based on the factors described above, so the actual starting annual base salary may be above or below this range. Benefits Inflection AI values and supports our team’s mental and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include: Diverse medical, dental and vision options 401k matching program Unlimited paid time off Parental leave and flexibility for all parents and caregivers Support of country-specific visa needs for international employees living in the Bay Area Interview Process Apply: Please apply on Linkedin or our website for a specific role. After speaking with one of our recruiters, you’ll enter our structured interview process, which includes the following stages: -Hiring Manager Conversation – An initial discussion with the hiring manager to assess fit and alignment. -Technical Interview – A deep dive with an Inflection Engineer to evaluate your technical expertise. -Onsite Interview – A comprehensive assessment, including: A domain-specific interview A system design interview A final conversation with the hiring manager Depending on the role, we may also ask you to complete a take-home exercise or deliver a presentation. For non-technical roles, be prepared for a role-specific interview, such as a portfolio review. Decision Timeline We aim to provide feedback within one week of your final interview.

Job Details Job Type

full-time

Experience Level

mid

Salary Range

$170,000 - $300,000

Location

Palo Alto, CA