As an AI Engineer, you'll develop and optimize LLMs, collaborating closely with cross-functional teams to enhance detection engineering capabilities and drive new AI initiatives.
Build the AI that makes detection engineers 10x more effective. Create cutting-edge LLM research to power our detection engineering community.
At Detections.ai, we're on a mission to 10x detection engineers. Security teams today are drowning in noisy tools and patchwork workflows. We're changing that—by building intuitive, AI-powered experiences that streamline how detection engineers write, test, and manage detections.
We combine deep expertise in cybersecurity, real-time systems, and applied AI to rethink how detection work gets done—from the ground up. Our team thrives on ownership, speed, and building for real users.
What You'll Do
We're looking for an AI LLM Engineer to drive the development and optimization of large language models that power our intelligent detection engineering products. You'll research, design, and implement cutting-edge LLM capabilities—from retrieval-augmented generation to agentic workflows—bringing AI into the critical path of security operations.
You'll:
- 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
You're a fit if you:
- 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
You'll stand out if you:
- 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
Our Stack
- 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
Why Join Us?
- 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
Ready to apply cutting-edge AI research to real-world security challenges? Show us what you've built with LLMs and tell us how AI can revolutionize detection engineering.
- Apply now to help us build the future of AI-powered security tooling.
Similar Jobs
Fintech • Machine Learning • Payments • Software • Financial Services
Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize LLM performance and scalability, partner with cross-functional teams, and contribute technical vision and roadmap for foundational AI systems.
Top Skills:
Aws UltraclustersC#C++GoHugging FaceJavaNemo GuardrailsPythonPyTorchScalaVectordbs
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Design and build the agent execution harness and orchestration runtime to enable reliable, observable, and scalable agentic AI in production. Own fault tolerance, latency, throughput, prompt/version management, LLM integration, evaluation frameworks, and technical leadership to ensure safe, cost-efficient multi-step agent workflows at enterprise scale.
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Use advanced analytics, statistical techniques, and machine learning to extract insights from large datasets. Design data solutions and pipelines, build predictive models (R, MATLAB), and apply TensorFlow and Scikit-Learn for deep learning and NLP. Collaborate with teams and clients, deliver quality work, and adhere to firm standards.
Top Skills:
MatlabRScikit-LearnTensorFlow
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
