Senior Software Engineer, Agentic AI at Invicti Security

Boston, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

03 May, 26

Salary

0.0

Posted On

02 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Agentic AI, Multi-Agent System Development, MCP Integrations, LLM Prompt Engineering, RAG Systems, Memory Architectures, End-to-End Ownership, Cross-Team Collaboration, AI/ML Capabilities, Distributed Systems, API Design, Cloud-Native Architectures, Prompt Engineering, Embeddings, Vector Databases

Industry

Computer and Network Security

Description

Who You Are: 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 Need: 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 What You’ve Got: Strong problem-solving mindset with intellectual curiosity about AI/ML High degree of ownership, accountability, and initiative Comfortable working in fast-paced environments where prototypes are rapidly iterated or discarded Excited about autonomous AI systems and seeing your work used by real customers Adaptable and effective working across distributed teams Detail-oriented, with a focus on delivering systems that scale and last Why Invicti:Your Health & Wellness Matters: Health Insurance: We cover 100% of employee health care, vision, and dental premium costs. For dependents, we contribute 75% of healthcare and 50% vision/dental premium cost. Coverage is effective on your first day. Employee Assistance Program: Emotional support counseling services — 24/7 life coaching, dependent care, elder care, financial & legal support, wellness coaching, new parent support, and more Parental Leave: 16-week paid leave for birthing parent recovery; 4-week paid leave for non-birthing/bonding parent 401(k) Savings Plan: 50% up to 6% company match with 100% annual cliff vesting We Value Work/Life Balance: Hybrid Flexible Schedule Discretionary Time Off: Take time away from work when you need it (subject to manager approval) Quarterly Thrive-Wellness Days: One extra day per quarter where the entire company takes a break to refresh and rejuvenate Volunteerism Time Off: 5 days of paid time off each year to participate in volunteer activities of your choice We Value You: Learning & Development Budget: Investment in your professional growth Employee Recognition: Ongoing recognition & rewards in a culture that emphasizes personal and professional growth At Invicti, we embrace diversity and individuality in all forms. Discrimination has no place here - regardless of race, religion, gender, age, ability, sexual orientation, or any other aspect that makes you unique. We're all about creating a space where everyone feels valued and included. So come as you are and join us in shaping the future of our industry.

Responsibilities

Design and implement autonomous agent systems and create integrations connecting various security tools. Collaborate with product and security teams to deliver capabilities that address real customer problems.