The AI Engineering Lead at Bricklayer AI is a hands-on technical leadership role driving the development of their agentic SOC platform. This position blends cutting-edge AI innovation with practical engineering solutions, focusing on building and implementing Retrieval-Augmented Generation (RAG) systems, AI agent frameworks, and prompt engineering for advanced models like GPT-4 and Claude. The role requires expertise in Python, AI frameworks (e.g., LangChain), vector databases, cloud infrastructure, and REST API development. Reporting to the CTO, the candidate will lead a technical team, mentor engineers, prototype new technologies, and optimize system performance for scalable AI-driven cybersecurity solutions.
Description
About Bricklayer AI
Bricklayer AI is the first AI cybersecurity solution that enables autonomous AI agents to work alongside human experts, to run a smarter, faster, and more effective security operations team. With Bricklayer AI, multiple independent AI agents collaborate with each other and their human counterparts to accomplish complex cybersecurity procedures, all controlled using natural language. Bricklayer technology features a unique modular design, multi-agent workflows, and no-code integrations that deliver the most intelligent and trustworthy AI results. Bricklayer empowers organizations to run the most optimized SOC imaginable with the people they already have.
The Position
Our AI Engineering Lead will serve as the hands on technical lead for our AI engineering initiatives, driving the implementation of our agentic LLM and Retrieval Augmented Generation (RAG) based autonomous SOC platform. This role combines hands-on technical team leadership expertise with strategic innovation and reports directly to the CTO. The ideal candidate will bridge the gap between cutting-edge AI capabilities and practical engineering solutions. They will put forth innovative ideas and prototypes to push our autonomous SOC solution forward. This leader will be comfortable working through ambiguity and will be extremely customer focused. They have worked in a startup environment before and are familiar with shipping often and iterating quickly.
Responsibilities
- Design and implement production-grade AI systems using OpenAI and Anthropic models
- Lead prompt engineering initiatives and develop RAG architectures
- Architect vector database solutions for efficient information retrieval
- Build and maintain AI agents using modern frameworks
- Guide technical decisions around AI infrastructure and tooling
- Mentor team members and establish AI engineering best practices
- Evaluate emerging AI technologies and recommend adoption strategies
- Optimize system performance and manage infrastructure costs
- Collaborate with stakeholders to translate business requirements into technical solutions
- Build innovative prototypes to vet new technologies and move the team forward
Qualifications
Required
- 5+ years of software engineering experience with 2+ years in AI/ML
- Expert-level knowledge of prompt engineering for GPT-4 and Claude models
- Proven experience building RAG systems
- Deep expertise in Python and AI frameworks (LangChain, LangGraph, AutoGen, Crew.ai)
- Strong background in AI agent development and orchestration
- Experience with vector databases (Pinecone, Pgvector, ChromaDB)
- Experience with REST API development using Django Rest Framework or similar
- Proficiency in cloud infrastructure (AWS/Azure) and containerization
- Track record of deploying production AI systems
- Experience leading technical teams
Preferred
- Advanced degree in Computer Science, AI, or related field
- Background in Cybersecurity applications
- Contributions to open-source AI projects
- Background in ML/DL fundamentals
- Experience with LLM fine-tuning and optimization