We are seeking a Senior AI Engineer to join our companys core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within our companys Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
Responsibilities
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.
Requirements: Must-have:
5+ years of experience in backend or AI engineering with strong coding skills (Python preferred).
Proven experience building and deploying production-grade AI/ML systems.
Strong software engineering fundamentals (data structures, algorithms, system design).
Experience with distributed systems, microservices, and cloud platforms (AWS/GCP/Azure).
Hands-on experience with LLMs and generative AI, including prompt engineering and model integration.
Experience with LLM frameworks and agent orchestration tools (e.g., LangChain, CrewAI, ADK, or similar).
Strong debugging and problem-solving skills, with an ownership mindset.
Nice-to-have:
Experience with ML frameworks such as PyTorch or TensorFlow.
Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD for ML).
Background in NLP, LLM optimization, or agent-based systems in production.
Experience with large-scale data pipelines and NoSQL databases.
Experience with model evaluation, monitoring, and continuous improvement in production environments.
Contributions to open-source projects or research publications.
This position is open to all candidates.