Artificial Intelligence Engineer
Location: California, United States - Remote
Department: Engineering
Location Type: REMOTE
Employment Type: FULL_TIME
- Implement, fine-tune, and optimize state-of-the-art LLMs for performance, accuracy, and security use cases
- Design and evaluate prompting strategies, flows, and application logic for LLM-powered features
- Build and integrate advanced capabilities such as RAG, function calling, and code interpreter technologies
- Design and deploy scalable ML pipelines for both batch and real-time use cases
- Collaborate closely with ML engineers, product teams, and detection engineers to align AI capabilities with business goals
- Lead the incubation of new AI initiatives and drive strategic technology choices in a microservices architecture
- Stay current with the latest research in LLMs, agents, and large-scale training methods, applying insights directly into production systems
- Document methodologies, models, and results to share across the team and company
- Have 5+ years of experience in NLP, machine learning, or data science
- Are strong in Python (R is a plus) and deep learning frameworks (e.g., PyTorch, TensorFlow)
- Have hands-on experience building, testing, and deploying LLMs such as GPT-4, Gemini, or similar
- Understand model training techniques, including data/model parallelism and distributed training
- Are comfortable with cloud-native infrastructure (AWS or GCP) and distributed computing
- Have experience with DevOps/MLOps/LLMOps practices
- Thrive in a high-context, low-process environment
- Hold a Master's or PhD in Computer Science, AI, or related fields
- Have experience building GenAI solutions using RAG frameworks or LLM agentic applications
- Bring direct experience applying AI in cybersecurity workflows
- Have strong research-to-production skills, bridging advanced ML concepts into deployable systems
- Frontend: React.js, Tailwind CSS, TypeScript
- Middle layer: Node.js, TypeScript
- Backend: Python (FastAPI)
- Infra & DevOps: AWS, GCP, Docker, Terraform, GitHub Actions
- Data: OpenSearch, DynamoDB
- AI Agents: Gemini, Anthropic, OpenAI
- Tooling: Figma, Storybook, CI/CD pipelines
- Build for real users: Work hand-in-hand with detection engineers
- Own meaningful problems: Ship features that matter
- Move fast, without red tape: Small, high-context team
- Make an outsized impact: You'll help shape both product and culture
- Apply now to help us build the future of AI-powered security tooling.
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