Senior Full Stack Engineer, Agentic Security

Dynamo AI•San Francisco, CA

1d•Remote

About The Position

You'll build and own the production systems behind Agent Warden - the backend services, frontend dashboards, CLIs, and deployment infrastructure that make the product work end-to-end. You'll ship features fast, keep things simple, and make the systems reliable enough for enterprise customers to depend on. This is a full stack, backend heavy role with a strong agentic development philosophy. We develop using AI-assisted workflows (Cursor, Claude Code, agent skills) as a first-class part of how we build software - not as an afterthought. You'll be expected to be highly productive in this mode of working.

Requirements

Strong full-stack experience - comfortable building APIs, writing database queries, and shipping React/Next.js UIs
Experience building production services with FastAPI or similar frameworks
Understand dependency management and packaging - comfortable with uv, pyproject.toml, editable installs, and managing dependency graphs across shared libraries
Owned release cycles end-to-end - versioning, changelogs, binary packaging, and distribution
Comfortable with infrastructure: Docker, Kubernetes, Helm, GitHub Actions, AWS. Can read a Helm chart, debug a failed deploy, and add an environment variable without hand-holding
Develop using AI-assisted tools (Cursor, Claude Code, Copilot) and be productive in agentic workflows - writing skills, using structured prompts, and leveraging AI to move faster. No AI slop.
Care about code quality, clear abstractions, and keeping things simple. Prefer explicit over clever.
Working knowledge of Git and comfortable with trunk-based development, rebasing, and clean commit hygiene
Comfortable working in ambiguity - requirements change fast, priorities shift, and proactive about figuring things out rather than waiting for direction
Communicate clearly and can own a feature end-to-end - from understanding the requirement to deploying it

Nice To Haves

Experience building CLIs with clean argument parsing, help text, and user-friendly error handling
Understanding of Model Context Protocol (MCP), have built MCP servers/clients, and understand how LLMs invoke tools and interact with external systems
Experience with Redis Streams, event-driven architectures, or real-time data pipelines
Experience with ArgoCD, GitOps workflows, or managing multi-environment deployments
Interest in AI security - understanding how agentic systems can be exploited and how to defend against it

Responsibilities

Own end-to-end multiple backend services - APIs, data pipelines, shared libraries, and ML-adjacent packages (Python, FastAPI, NestJS)
Build frontend dashboards and UIs with clean DOM rendering, efficient state management, and solid UX principles (React, TypeScript)
Design and work with data models and migrations (PostgreSQL), and caching layers (Redis)
Contribute to CI/CD and deployment infrastructure (Dockerfiles, Helm charts, GitHub Actions, K8s, AWS) and own release cycles end-to-end - versioning, binary packaging (PyInstaller), and distribution
Write and use agent skills, cursor rules, and structured AI-assisted workflows as part of your daily development process
Own the quality of what you ship - unit tests, latency tests, performance benchmarks, load tests, and debugging production issues
Collaborate closely with the Applied Research team to productionize new capabilities