Senior AI Software Engineer

Confirmed live in the last 24 hours

SentinelOne

Compensation

$132,000 - $209,300/year

United States - Remote

Remote

Posted April 2, 2026

Job Description

Our Purpose

At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.

About Us

SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.

Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.

What Are We Looking For?

We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.

As a Senior AI Software Engineer you will build and maintain Python backend services that support AI-powered features and workflows. Using tools like FastAPI, you’ll design scalable, high-performing systems with a focus on reliability and real-world use. You’ll own projects end-to-end, from design through deployment, delivering solutions for both customers and internal teams.

What will you do?

Design, build, and operate backend services in Python that power AI-driven products and shared capabilities.
Build and maintain resilient service integrations across internal and external systems, handling failure modes, rate limits, and interface changes.
Own ambiguous, end-to-end problems: from early design and architecture through implementation, rollout, and iteration in production.
Develop and evolve LLM-backed features and agentic workflows used in production, with a focus on reliability, observability, and real-world behavior.
Contribute to core AI platforms and enablement systems—services that your team uses directly and that other engineers can build on.
Collaborate with product managers, researchers, and other engineers across teams to turn loosely defined AI use cases into concrete, production-ready systems.
Help shape evaluation and quality strategies for AI-powered features, including building or extending evaluation harnesses, benchmarks, or feedback loops.
Act as a technical leader for the work you own—making sound design decisions, coordinating with stakeholders, and contributing to design and code reviews.

What skills and experience should you bring?

A degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
4+ years of experience building and shipping production backend software (Senior or Staff level, depending on experience and impact).
Excellent modern Python engineering skills, with the ability to work effectively in distributed, asynchronous environments.
Strong system design skills, including the ability to write clear design docs and solution specifications that align stakeholders and drive sound architectural decisions.
Demonstrated ability to shepherd work from concept through production in complex, evolving environments.
Proven experience designing and implementing integrations across multiple systems in production environments.
Hands-on experience shipping and operating LLM- or generative-AI–backed features or services as part of larger production systems.
Excellent communication skills and a collaborative approach in globally distributed teams.