Senior Backend Software Engineer - GenAI

About The Role

Enterprises of all sizes trust Abnormal Security’s cloud products to stop cybercrime. Being effective at stopping cybercrime, due to its adversarial nature, requires a high level of agility to respond to threats. Our Research and Development organization is forming a group to develop advanced AI-powered security products at Abnormal, creating innovative solutions for customers while supercharging internal processes.

The Gen AI Group (GAI) is at the forefront of developing next-generation AI-based solutions that will transform our customer-facing products and internal applications. As a Senior Software Engineer in the GAI, you will play a pivotal role in architecting, developing, and deploying advanced AI technologies to solve complex problems identified working with senior engineering leaders including our CTO and Chief Architect. This position requires a blend of technical expertise, innovative thinking, and leadership skills to drive the development of cutting-edge AI solutions.

About You

Want more jobs like this?

Get jobs that are Remote delivered to your inbox every week.

Get Jobs

Send me The Muse newsletters for the best in career advice and job search tips.

By signing up, you agree to our Terms of Service & Privacy Policy.

• Are passionate about leveraging AI to solve real-world problems and can demonstrate innovative thinking in AI applications.
• Have a strong track record of leading technical projects and mentoring other engineers.
• Enjoy working on complex problems and can adapt to rapidly changing environments.
• Thrive in collaborative settings and are eager to work with cross-functional teams to achieve common goals.
• Are excited about the opportunity to shape the future of AI-powered security products and make a significant impact in the cybersecurity industry. 

What You Will Do 

• AI Solution Development: Design, develop, and implement advanced AI models and algorithms to solve identified problems, ensuring they meet performance, scalability, and reliability requirements.
• Technical Leadership: Provide technical guidance and mentorship to junior engineers within the team, fostering a collaborative and innovative work environment.
• Research & Innovation: Stay abreast of the latest advancements in AI and machine learning technologies, incorporating relevant techniques and methodologies into the development process.
• Collaboration: Work closely with the CTO, Chief Architect, and other stakeholders to understand business needs and translate them into technical solutions.
• Code Quality & Best Practices: Ensure the highest standards of code quality, documentation, and best practices are maintained across the team.
• System Architecture: Contribute to the architecture and design of AI systems, ensuring they are robust, maintainable, and aligned with the overall technical strategy of the organization.
• Performance Optimization: Analyze and optimize AI models and systems for efficiency, performance, and scalability.
• Integration: Collaborate with other engineering teams to integrate AI solutions seamlessly into existing products and systems.

This is a leadership role on the team and you will be expected to contribute both code and guidance to the team: you will be accountable for delivering great solutions and simultaneously making the team around you better.

Must Have

• Minimum of 8 years of experience in software engineering with a focus on AI/ML.
• Proven track record of delivering AI-based solutions in a production environment.
• Experience with AI/ML frameworks and tools such as TensorFlow, PyTorch, Scikit-learn, etc.
• Backend generalist with both breadth and depth of experience with several backend architectures (streaming, event driven, RPC-based, serverless, etc.) and technologies (data stores, caches, RPCs, etc.)
• Strong programming skills in languages such as Python or Go
• Proven track record mentoring engineers and “raising the bar” for the whole team
• Independent and self-motivated

Nice To Have 

• Experience with big data technologies and tools such as Hadoop, Spark, or similar.
• Knowledge of reinforcement learning, computer vision, or other specialized AI domains.

#LI-ML1