🌍 We’re making security suck less for developers.
Security tools haven't kept pace with modern software development. They interrupt teams, slow releases, and turn security into a bottleneck. Aikido is changing that. We build developer-first security products that reduce real risk without getting in the way of shipping software. We focus on what matters, automate the rest, and make security a capability, not a blocker.
Founded in 2022 by third-time founders, Aikido has $85M in the bank and the runway to build for the long term.
Following our acquisition of Root.io in June 2026, the team formed Agentic Factory: the business unit moving beyond vulnerability detection to automated remediation.
We are looking for an AI Engineer to build the systems that drive this: AI agents that investigate vulnerabilities, generate and validate code fixes, and continuously refine their performance. In this role, you’ll work at the intersection of AI engineering, security automation, and rigorous evaluation to translate cutting-edge models into dependable production tools.
Responsibilities
Build and evolve production AI agent pipelines for CVE research, patch generation, validation, container image remediation, and end-to-end merge requests.
Design the agent capabilities behind those workflows: prompts, tools, model selection, context, guardrails, and integrations.
Build the feedback loops that make our systems better: tracing production runs, creating datasets, defining evals and scorers, and using results to guide iteration.
Analyze real-world performance to answer the questions that matter: Did this change improve patch success, quality, latency, or cost? Can we prove it?
Operate what you build in production across Kubernetes, Argo Workflows, AWS, and GitOps.
Partner closely with Product and engineering to focus on the customer problems with the highest security impact—and ship quickly.
Hands-on experience building with LLMs, agentic architectures, and AI workflows—such as LangGraph, Claude Agent SDK, OpenAI Agents SDK, or equivalent.
Strong experience using coding agents such as **Claude Code, Codex, or Cursor** as part of your day-to-day engineering workflow.
A solid grasp of the mechanics of data science and applied AI: evaluation design, experimental rigor, noisy metrics, statistical reasoning, feedback loops, and evidence-based decision-making.
The judgment to distinguish an impressive demo from a system that reliably works in production.
Strong software engineering skills and an experiment-driven mindset: form a hypothesis, build, measure, learn, and iterate.
Comfort working independently in a fast-moving environment with high ownership and little unnecessary process.
Clear communication and good product instincts.
Nice to have
Experience in cybersecurity: CVEs, containers, software supply chain security, or pentesting.
Experience working with open-weight models, including model selection, serving, inference optimization, or fine-tuning.
Familiarity with Langfuse or similar observability and evaluation platforms.
Experience with Go or TypeScript.
What you can expect
Short decision lines and meaningful ownership from day one.
The freedom to shape important projects and ship quickly.
Top-tier compensation and equity.
High trust, strong values, and no corporate theatre.
Flexible working hours and an open, informal culture.
Our stack: Python, LangGraph, Claude Agent SDK, Langfuse, Kubernetes, Argo Workflows, AWS, GitOps, and MCP.
Summary
Build and operate production AI agent pipelines that investigate vulnerabilities and generate validated code fixes. Design agent prompts and tools, and build tracing and evals to measure patch success, quality, latency and cost. Requires LLM and agentic framework experience and use of coding agents such as Claude Code or Cursor.
Responsibilities
Build and evolve production AI agent pipelines for CVE research, patch generation, validation and merge requests; design agent prompts, tools, model selection and guardrails; build tracing, datasets and evals; analyze production performance; operate systems on Kubernetes, Argo Workflows, AWS and GitOps; partner with Product and engineering
Qualifications
LLM and agentic architecture experience (LangGraph, Claude Agent SDK or equivalent); strong use of coding agents (Claude Code, Codex, Cursor); evaluation design and statistical reasoning; judgment to separate demos from reliable production systems; strong software engineering; clear communication
Experience requirements
Hands-on experience building with LLMs and agentic AI workflows; comfort working independently in a fast-moving environment with high ownership
Benefits
Top-tier compensation and equity; flexible working hours; high trust, strong values, open informal culture