Procore Technologies
From Procore Technologies's careers page
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Senior Security Engineer We’re looking for a Senior Security Engineer to join Procore’s Security Engineering team.
Senior Security Engineer
We’re looking for a Senior Security Engineer to join Procore’s Security Engineering team. In this role, you won’t just be a gatekeeper; you will be a builder of autonomous systems. You will be responsible for designing and deploying the foundational AI agents that protect our platform, data, and users. Your primary goal is to move beyond manual oversight to build a self-healing, resilient cloud infrastructure powered by agentic workflows.
As a Senior Security Engineer, you’ll partner with Product & Technology, IT, GRC, and Security Operations to integrate autonomous security into the very fabric of our systems. You will use your expertise in security, software development, and LLM orchestration to build agents that can reason through threats, remediate control findings in real-time, and enforce identity boundaries. This is a critical role in redefining what "secure by default" means in an AI-driven SaaS ecosystem - Apply today.
This position reports into the Senior Manager, Security Engineering and will be based in our Bengaluru office.
At Procore, AI isn’t a specialized tool, it's a core competency. We expect every team member to be AI-literate, leveraging generative tools and agentic workflows to move faster and work smarter. You won’t just use AI; you’ll be building the agentic future of construction.
Build Autonomous Defenders: Design and deploy security agents using frameworks like LangChain, CrewAI, or AutoGPT to automate complex security reasoning tasks.
Architect Agentic IAM: Build autonomous guardrails for cloud (AWS) and corporate environments that dynamically adjust permissions based on agentic analysis of risk telemetry.
Agentic SDLC Integration: Construct automated pipelines where AI agents perform continuous threat modeling, code analysis, and auto-generate PRs for vulnerability remediation.
Secure the AI Lifecycle: Develop and implement security controls for our internal AI agents, including Prompt Injection mitigation, RAG security, and sandboxed execution environments.
Self-Healing Infrastructure: Develop "paved road" libraries and autonomous agents that monitor and fix drift in containerized (Kubernetes, EKS) and IaC (Terraform) workflows.
Autonomous Asset Intelligence: Build agentic workflows for real-time asset discovery and automated SBOM generation that adapts as our ecosystem evolves.
Lead the Technical Roadmap: Contribute to the vision of "Agentic SecEng," moving the organization from manual dashboards to autonomous response.
Mentor & Code Review: Review agent logic, prompt templates, and traditional code, mentoring junior engineers in the transition from security analysts to security builders.
The Builder Mindset: Bachelor's degree in Computer Engineering or equivalent; you identify as a Software Engineer first, with a deep specialization in Security.
Agentic Expertise: Proven experience building, testing, and deploying AI agents in production. You understand the nuances of ReAct patterns, tool-calling, and agentic memory.
Software Mastery: Professional-grade coding skills in Python or Go. You should be comfortable building complex distributed systems, not just simple automation scripts.
Modern AI Stack: Deep familiarity with LLM orchestration (LangChain, Semantic Kernel), Vector Databases (Pinecone, Weaviate), and LLM security frameworks.
Cloud & Orchestration: Strong hands-on experience with AWS security services and Kubernetes, particularly in building secure, isolated environments for AI agent execution.
Engineering DevSecOps: A track record of building security automation within CI/CD pipelines, with a shift toward autonomous "Human-in-the-loop" remediation.
Security Domain Depth: While we prioritize building, you must have a solid foundation in data protection (encryption/KMIP) and identity (OIDC, OAuth 2.0).
Prompt Engineering as Logic: Ability to design robust, version-controlled prompts that treat AI reasoning as a predictable, testable engineering component. Communication: The ability to explain "Agentic Thinking" to cross-functional teams and negotiate the balance between autonomous action and system stability.
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