AI/ML Engineer

Brio Digital; California (MO); Remote; USD 120,000 - 180,000; Full time

Job summary

Join a forward-thinking technology company as a Senior AI Product Engineer, where you will lead the development of innovative AI-driven workflows for security operations. This role involves creating autonomous systems that enhance real-time detection and response capabilities in cloud-native environments. You'll collaborate with product and UX teams to deliver user-friendly AI experiences while optimizing performance based on real-world feedback. Be part of a mission-driven team focused on solving critical security challenges with next-gen AI products, all within a high-velocity remote work environment.

Benefits

Competitive compensation

Equity offering

Remote work flexibility

Opportunity to shape AI products

Qualifications

• 5+ years of AI/ML engineering experience with a focus on security.
• Proven ability to build LLM-integrated systems using various platforms.

Responsibilities

• Build AI agents to enhance security operations like incident triage.
• Design multi-agent systems for log analysis and policy enforcement.

Skills

AI/ML Engineering

Python

Kubernetes

LLM Integration

Security Automation

Collaboration Skills

Tools

LangChain

OpenAI

Hugging Face

AWS SageMaker

PyTorch

Transformers

Job description

Job Title: Senior AI Product Engineer

Location: Remote (Canada, USA or LATAM)

About the Company

We are a high-growth technology company focused on advanced threat detection in cloud-native environments. By leveraging system-level telemetry and AI automation, we enable clients to detect anomalies, insider threats, and zero-day attacks with unmatched precision.

The Role

We're hiring a Senior AI Product Engineer to lead innovation at the intersection of machine learning, intelligent agents, and security infrastructure. You will develop AI-driven workflows and autonomous systems that support real-time detection, triage, and remediation in containerized and cloud-based ecosystems.

Responsibilities

• Build AI agents and intelligent systems that enhance or automate security operations like incident triage, alert classification, and threat response.
• Design and implement collaborative multi-agent systems to perform log analysis, deduplication, root cause identification, and policy enforcement.
• Ensure agents operate autonomously and safely, interacting effectively with real-time data and APIs.
• Develop features for automated explainability, threat analysis, and recovery suggestions using tools such as retrieval-augmented generation (RAG) and LLMs.
• Work with product and UX teams to deliver clear, user-friendly AI experiences.
• Optimize agent performance and reliability using real-world feedback, telemetry, and iterative evaluation.
• Explore and implement cutting-edge AI agent orchestration frameworks and memory management solutions.
• Monitor production performance, ensuring secure, cost-effective, and scalable deployments.
• Contribute to internal standards for AI safety, auditability, and fault tolerance.

Requirements

• 5+ years of experience in AI/ML engineering, ideally with exposure to security, developer platforms, or automation.
• Proven background building LLM-integrated systems using platforms like LangChain, OpenAI, Hugging Face, or equivalents.
• Skilled at deploying production AI solutions with considerations for performance, security, and cost.
• Product-focused mindset with a strong bias toward practical, customer-impacting outcomes.
• Experience working with Kubernetes, containers, and optionally eBPF or IAM technologies.
• Proficient in Python; knowledge of Go or similar backend languages is a plus.
• Comfortable with experimentation and iterative development based on measurable outcomes.
• Excellent collaboration and communication skills.

Preferred Experience

• AI agent frameworks: LangGraph, CrewAI, AutoGen, etc.
• AI platform experience: managed model serving on cloud services like AWS Bedrock or SageMaker.
• Model training and pipeline components: PyTorch, Transformers, vector stores (e.g., Pinecone, Weaviate).
• AI observability tools such as WandB, Arize AI, PromptLayer.
• Kubernetes, container orchestration, and infrastructure-as-code experience.
• Knowledge of runtime security, threat analysis, or response automation is a plus.
• Understanding of vector databases and RAG-based pipelines.
• Familiarity with LLMOps, GPU inference, and cost-aware orchestration.

Why Apply

• Develop next-gen AI products that solve real security challenges.
• Be part of a mission-focused, high-velocity remote team.
• Competitive compensation and equity offering.
• Opportunity to shape the future of AI in cloud infrastructure.