Inflection AI is a public benefit corporation leveraging our world class large language model to build the first AI platform focused on the needs of the enterprise.
Who we are:
Inflection AI was re-founded in March of 2024 and our leadership team has assembled a team of kind, innovative, and collaborative individuals focused on building enterprise AI solutions. We are an organization passionate about what we are building, enjoy working together and strive to hire people with diverse backgrounds and experience.
Our first product, Pi, provides an empathetic and conversational chatbot. Pi is a public instance of building from our 350B+ frontier model with our sophisticated fine-tuning (10M+ examples), inference, and orchestration platform. We are now focusing on building new systems that directly support the needs of enterprise customers using this same approach.
Want to work with us? Have questions? Learn more below.
As a Member of Technical Staff, Backend Engineer, you will be instrumental in unblocking critical projects and developing robust backend services. You’ll work primarily in Python and TypeScript/Node to build and maintain the tools and systems that power our inference pipelines, data tools, and security frameworks. While deep ML expertise isn’t required, a willingness to learn and a basic familiarity with ML workflows will be highly valued.
This is a good role for you if you:
- Have strong backend engineering experience, particularly in Python and/or TypeScript/Node.
- Are comfortable developing reliable, scalable backend systems that can integrate with diverse technology stacks.
- Enjoy solving programming challenges and are eager to expand your knowledge of ML-related infrastructure.
- Are a proactive problem solver who can work independently while collaborating effectively with cross-functional teams.
- Believe in the impact of robust backend infrastructure on the success of enterprise-grade AI solutions.
Responsibilities include:
- Designing, developing, and maintaining backend services and tools to support our ML inference pipelines, data tools, and security systems.
- Collaborating with teams across the organization to integrate backend solutions seamlessly with our front-end and ML components.
- Ensuring high levels of scalability, reliability, and security in the systems you build.
- Participating in code reviews, testing, and documentation efforts to maintain our high-quality software standards.
- Continuously learning about ML workflows and contributing innovative ideas to further enhance our AI platform.
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
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.