---
title: 'Artificial Intelligence Engineer at detections.ai'
canonical: 'https://feeny.ai/job/artificial-intelligence-engineer-detections-ai-california-xhphez3sxn7k'
type: 'job'
last_seen: '2026-09-05'
---

# Artificial Intelligence Engineer at detections.ai

- **Company:** detections.ai
- **Location:** California, United States
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2025-08-28
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.gem.com/detections-ai/am9icG9zdDqBdM-fHC046DK7qT_ti59L

## Job description

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.

## About detections.ai

## Company Overview
- **One-liner**: A community-driven platform for detection engineers to share, discover, and build security detections across multiple SIEM languages.
- **Entity Type**: Private (Seed stage; Seed round in November 2025 led by Modern Technical Fund)
- **Headquarters**: San Francisco, California, United States
- **Founded**: Not publicly available (seed round in 2025 suggests a very early-stage startup)
- **Founders**: Prasanth Ganesan (Co-Founder & CTO) – other co-founders not publicly named

## Core Business
- **Primary industry**: Computer and Network Security (Detection Engineering)
- **Target customers**: B2B – detection engineers, security operations teams, enterprises running SIEM/EDR platforms
- **Mission or purpose**: "Building better detections, together" – a world where detection engineers collaborate openly, knowledge compounds, and no one solves the same problem twice.

## Products & Services
- **Community Platform (Free, Forever)**: Browse 20,000+ community-contributed detections in languages including Sigma, KQL, SPL, YARA, YARA-L, S1QL, Cortex QL, CQL, and Suricata. Save, publish, and translate across 9 languages.
- **AI Assistant**: Paste a threat intel report, blog post, or threat actor profile; AI drafts a detection and refines logic iteratively. Also translates detections between SIEM formats while preserving logic.
- **Intel Exchange**: Structured threat reports scored on actionability (1-10) linked to existing detections and CVEs. Publicly browseable.
- **Enterprise** (launched July 2026): Private team workspace, governance, coverage tracking across multiple SIEMs, AI Agents that audit for drift, staleness, noise, and overlap. Deploy back to SIEMs. Coverage reports.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding – Seed round (November 2025) from 3 investors led by Modern Technical Fund; amount not disclosed
- **Notable Investors/Partners**: Modern Technical Fund (lead), plus two other unnamed investors. No strategic partners publicly listed.
- **Growth Signals**: Headcount grew +533.3% YoY (15 employees as of mid-2026); 16,000+ detection engineers use the community; Enterprise launch with AI agents; webinars and growing contributor base; monthly website traffic up 16% (1,509 visits, small but growing).

## Competitive Advantages
- **Community-led library**: 20,000+ detections contributed by peers – network effects make the platform more valuable as more engineers join.
- **Multi-language translation**: Seamlessly convert detections between 9 SIEM languages (Sigma, KQL, SPL, YARA-L, etc.) without manual porting.
- **AI-assisted detection generation**: Reduces time from threat intel to working detection – "coverage before lunch".
- **MITRE ATT&CK mapping**: Coverage visibility across the entire detection stack.
- **Open platform**: Free tier for individual contributors encourages widespread adoption and community trust.

## Strategic Focus
- **Enterprise adoption**: Monetizing the community platform with a paid Enterprise tier that adds governance, AI agents, and coverage tracking.
- **AI agent expansion**: Continuous auditing and tuning of detection libraries to reduce noise and drift.
- **Growing the contributor base**: Encouraging high-quality submissions through contributor features (subscriptions, webinars) to deepen the content moat.

## Why Work Here
- **Culture**: "Detection-obsessed" – a tight-knit team of domain experts passionate about collaborative security engineering. Emphasizes knowledge compounding and open sharing.
- **Remote-first**: Fully remote environment (employees in United States and Canada).
- **Growth stage**: Early-stage startup with rapid headcount growth (+533% YoY) – opportunity to shape product and culture.
- **Tech stack**: Modern tools including TypeScript, React, Python, PyTorch, Elasticsearch, Docker, GitHub Actions, and multiple cloud services (AWS likely).
- **Notable perks**: Not explicitly listed, but typical of seed-stage remote startups: flexible hours, equity, direct impact on product direction.

## Sources
1. [detections.ai](https://detections.ai)
2. [About – Detections AI](https://detections.ai/about)
3. [Built In – detections.ai](https://builtin.com/company/detections-ai)
4. [LinkedIn – detections.ai](https://linkedin.com/company/detectionsai)
5. [Gem Careers – detections.ai](https://jobs.gem.com/detections-ai)

## Other roles at detections.ai

- [Marketing Manager](https://feeny.ai/job/marketing-manager-detections-ai-california-a3eb4yycks9v) — California, United States
- [Vice President of Engineering](https://feeny.ai/job/vice-president-of-engineering-detections-ai-california-z8nwe6yttgtt) — California, United States
- [Data Engineer](https://feeny.ai/job/data-engineer-detections-ai-california-yy7cb2nan10h) — California, United States
- [Frontend Developer](https://feeny.ai/job/frontend-developer-detections-ai-california-6mmhb82dxzbv) — California, United States
- [Artificial Intelligence Engineer](https://feeny.ai/job/artificial-intelligence-engineer-precision-ai-calgary-7pm3ctjayknf) — Calgary, Canada