Senior Software Engineer, Agentic AI

You're a seasoned software engineer ready for your next challenge. In this role, you'll join Invicti's newly formed AI team as a Senior Software Engineer, Agentic AI, and play a pivotal role in building our next-generation Agentic AppSec solution. As AI reshapes how software is built and how attackers exploit it, you'll help give defenders an edge by applying attacker-inspired techniques to solve modern security challenges. You design, build, and deliver software solutions rapidly, working across the stack from agent architectures and memory systems to integrations with security tools and developer workflows. You collaborate closely with product and security teams to deliver capabilities that solve real customer problems. You thrive in a high-ownership role on a small team, where your technical decisions directly shape the product, with an initial focus on agentic pentesting.

What You'll Be Doing:

• Multi-Agent System Development: Design and implement autonomous agent systems in Python using frameworks like AWS Strands Agents, with emphasis on orchestration, reasoning, and decision-making.
• MCP Integrations: Create Model Context Protocol integrations connecting Octo to security tools, developer environments, and AI coding assistants like Cursor and GitHub Copilot.
• LLM Prompt Engineering: Develop and refine prompt chains for real security use cases, including triage, prioritization, and remediation.
• RAG & Memory Systems: Build retrieval-augmented generation pipelines and memory architectures that give agents a persistent, contextual understanding of customer environments.
• End-to-End Ownership: Own features from design through production: build, test, deploy, and measure outcomes.
• Cross-Team Collaboration: Work closely with product, platform engineering, security research, and infrastructure teams to ensure we're building what customers need.
• Experimentation & Productization: Evaluate new AI/ML capabilities and determine how to bring them to production.

What You'll Bring:

• Hands-on experience building LLM-powered applications, RAG systems, or agentic AI.
• Strong Python proficiency.
• Understanding of distributed systems, API design, and cloud-native architectures.
• Experience with prompt engineering, embeddings, and vector databases.

Preferred:

• Experience with agent frameworks (AWS Strands, LangGraph, AutoGen, CrewAI) in production environments.
• Familiarity with MCP (Model Context Protocol) and AI tool integration patterns.
• Background in application security, pentesting, or offensive security.