Senior Engineer - AI-Driven Workflows

RADICL•Boulder, CO, CO

4d•$145,000 - $185,000•Hybrid

About The Position

RADICL is seeking a Senior Engineer to focus on AI-driven workflows and intelligent automation systems. You'll architect and build the next generation of automated incident response capabilities powered by advanced AI systems. This role is entirely focused on automation and workflow orchestration - you'll create intelligent systems that automatically process security data, generate insights, and execute response actions without direct human interaction in the critical path. You'll work on automated case management systems that combine large language models, threat intelligence, entity attribution analytics, and automated reasoning to accelerate incident response. Your work will directly impact how our platform automatically processes threats, correlates entity relationships, and executes response workflows at scale. Your focus will be on automated intelligence and case processing systems that consume security data feeds to drive autonomous security operations. If building AI systems that enhance human decision-making in high-stakes security environments excites you, RADICL is seeking high-performing, motivated individuals to join our mission. As an early member, you will work closely alongside an experienced founding team. You will work with the latest AI/ML technologies and cybersecurity platforms. You will have a significant impact on the growth of an innovative cybersecurity offering in the SMB space. You will receive an outsized equity grant and realize the life-changing experience of building a company. If the above excites you, RADICL Defense is seeking high performing, motivated individuals to join our mission. As an early member, you will work closely alongside an experienced founding team and realize the life-changing experience of building a company. You will work with the latest technologies in software, cybersecurity, and cloud and will have a significant impact on the formation of our platform and offering.

Requirements

AI/ML systems experience: 3+ years implementing production AI workflows, preferably with large language models, agent systems, or intelligent automation platforms
LLM integration: Hands-on experience with GPT, Claude, or similar models; understanding of prompt engineering, fine-tuning, and AI safety considerations
Event-driven architecture: Strong background in designing reliable, scalable systems using message queues (Kafka), stream processing, and asynchronous workflows
Go and Python proficiency: Experience building high-performance backend services in Go and AI/ML pipelines in Python; familiarity with frameworks like LangChain, LlamaIndex, or similar
Security domain knowledge: Understanding of automated incident response workflows, entity relationship modeling, threat attribution methodologies, and cybersecurity operations
Data systems: Experience with Elasticsearch/OpenSearch, PostgreSQL, and handling large-scale security data processing and analysis
Deterministic system design: Ability to build reliable, testable systems that incorporate AI feedback while maintaining predictable behavior and auditability
API design: Experience designing RESTful APIs and real-time interfaces (WebSockets, SSE) for automated AI workflow systems and data processing pipelines
Cloud platforms: AWS experience, particularly with Bedrock, Lambda, ECS, and other AI/ML services
Workflow automation: Understanding of business process automation, rule engines, and creating configurable, repeatable workflows
Testing AI systems: Experience with testing strategies for AI-powered applications, including prompt testing, model validation, and regression detection

Nice To Haves

MLOps experience with model deployment, monitoring, and lifecycle management
SOAR platform experience (Phantom, Demisto, etc.) or security orchestration background
Threat intelligence experience with automated IoC enrichment, entity correlation, MISP, STIX/TAXII, or threat attribution analytics
React/TypeScript for building AI-powered user interfaces
Vector databases and semantic search for security data correlation
Graph databases or knowledge representation for threat modeling

Responsibilities

Automated incident response — design and build intelligent case management systems that automatically triage security incidents, generate threat context reports, and execute response actions without human intervention in the critical path
Agentic workflow orchestration — develop sophisticated agent systems using large language models (LLMs) that autonomously reason about security data, correlate threat patterns, and execute complex investigation workflows
Deterministic automation pipelines — create reliable, event-driven systems that learn from AI feedback to improve decision-making, automate response actions, and ensure consistent incident processing at scale
Automated intelligence processing — create systems that consume security data feeds, automatically enrich indicators of compromise (IoCs), correlate threat intelligence, and generate actionable insights without manual intervention
Multi-modal data integration — develop systems that correlate structured security data, unstructured threat intelligence, and analyst feedback to continuously improve AI model performance and workflow reliability
Real-time streaming workflows — implement event-driven architectures using Kafka that process security alerts, enrich threat data, and trigger appropriate AI-driven responses in real-time
LLM integration and optimization — work with AWS Bedrock, Azure OpenAI, and other AI platforms to optimize model selection, prompt engineering, and cost-effective AI operations at scale