JR-166835 AI Engineer Senior

Job (Project) Description

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.

Locations

Brazil

Peru

Colombia

Argentina

Uruguay

Bolivia

Requirements

• 5+ years of production software development experience with a track record of shipping high quality solutions;
• Hands-on experience building LLM-powered applications, RAG systems, or agentic AI;
• Strong Python proficiency with solid software engineering fundamentals;
• Understanding of distributed systems, API design, and cloud-native architectures;
• Experience with prompt engineering, embeddings, and vector databases;
• End-to-end software development skills, including frontend development, building pipelines, tests, monitoring, and scalability;
• Ability to balance engineering rigor with pragmatic delivery, embracing agentic coding tools like Claude Code to accelerate delivery;
• Clear communication skills — you surface problems early and propose solutions.

What's 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, penetration testing, or security tooling;
• Experience with Go or C# for performance-critical components;
• Ability to build single-page applications using Vue.js;
• AWS experience with Bedrock and Kubernetes deployments;
• Familiarity with using GitLab for source control and CICD;
• Knowledge of evaluation methodologies for LLM systems (benchmarks, red-teaming, human feedback);
• Experience building third-party product integrations using REST APIs;
• Contributions to open-source AI/ML projects.

Job Responsibilities:

• 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 We Offer

• Competitive salary;
• 100% remote opportunity;
• Flexible work environment (in-office, remote, or hybrid depending on preferences and manager approval);
• Opportunities for professional growth and career advancement;
• Collaborative and innovative work environment;
• Paid time off, including holidays, vacation and sick leave;
• Benefits may vary by location and will be confirmed during the interview process.

JR-166835