Full-Time

Systems Engineer

Updated on 8/1/2026

Dedalus Labs

Dedalus Labs

11-50 employees

Cloud platform for agentic AI development

No salary listed

H1B Sponsorship Available

San Francisco, CA, USA

In Person

Relocation support is available.

Category
DevOps & Infrastructure (1)
Required Skills
Kubernetes
Rust
Distributed Systems
Git
Computer Networking
Operating Systems
Docker
Go
C/C++

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Requirements
  • Fluency in Go, C, C++, or similar systems languages.
  • Strong software engineering fundamentals.
  • Good understanding of operating systems, distributed systems, or networking concepts.
  • Ability to reason about performance, reliability, concurrency, and debugging.
  • Ability to navigate large systems with many moving parts.
  • High agency and strong engineering judgment.
  • Strong communication and collaborative instincts.
Responsibilities
  • Build distributed infrastructure for large-scale agent workloads.
  • Build virtualization and sandboxing systems.
  • Build persistent compute and storage primitives.
  • Build scheduling, orchestration, and reliability systems.
  • Build runtime infrastructure for long-running artificial intelligence agents.
  • Build internal developer platforms and tooling.
  • Build production systems operating under real-world scale, latency, and reliability constraints.
  • Build a distributed storage layer for persistent agent state.
  • Improve sandbox startup latency from seconds to milliseconds.
  • Design scheduling systems that efficiently allocate compute across thousands of concurrent agents.
  • Develop virtualization and isolation technologies for secure multi-tenant workloads.
  • Profile bottlenecks across networking, storage, scheduling, and runtime layers.
  • Build developer infrastructure that simplifies deploying and operating artificial intelligence agents.
Desired Qualifications
  • Experience with Kubernetes or modern cloud infrastructure.
  • Experience building distributed systems in industry, research, or open source.
  • Familiarity with distributed storage systems.
  • Understanding of consistency models and consensus.
  • Experience with virtualization, containers, hypervisors, or Firecracker.
  • Kernel, operating systems, or low-level runtime experience.
  • Contributions to systems-focused open source projects.
  • Experience with performance engineering and systems optimization.
  • Background in systems research, networking, databases, distributed computing, or related fields.
  • Experience operating production infrastructure at scale.

Dedalus Labs provides a cloud platform that acts as a drop-in MCP gateway, connecting any LLM to any MCP server with hosting, scaling, and a single API. Its OpenAI-compatible SDK lets developers orchestrate agentic AI workflows by routing between LLM providers and tools from a hosted MCP marketplace, without needing Docker or YAML configuration. The platform supports universal model access across models like GPT-4, Claude, and Gemini, and hybrid tooling that combines Python functions with pre-built MCP tools, along with serverless scaling and hot-reloading for production-ready deployments. It plans a marketplace for developers to monetize agents or servers with an 80% creator share and instant payouts, aiming to speed up AI development from weeks to minutes and simplify deployment, scaling, and monetization of agent-based AI workflows.

Company Size

11-50

Company Stage

Seed

Total Funding

$11.1M

Headquarters

San Francisco, California

Founded

2025

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Simplify Jobs

Simplify's Take

What believers are saying

  • DAuth enables secure credential handling without requiring developers to build custom security infrastructure.
  • The open-source MCP Authorization Server and zero-trust enclave architecture accelerate enterprise adoption of AI agents.
  • Integration with Smithery and Cloudflare gives SaaS vendors a direct path to serve AI agents without middlemen.

What critics are saying

  • WorkOS captured enterprise MCP authentication with full spec compliance, undercutting DAuth's security moat within 6–12 months.
  • TrueFoundry's unified AI Gateway replaces Dedalus's multi-product stack with a single control plane within 9–15 months.
  • Composio and Bifrost dominate lightweight MCP integration, eroding the '5 lines of code' simplicity advantage within 3–9 months.

What makes Dedalus Labs unique

  • Dedalus Labs provides the first secure, multi-tenant DAuth for MCP servers, solving critical authentication gaps.
  • Its 5-lines-of-code SDK and 3-click deployment reduce agent setup from weeks to minutes.
  • The platform supports vendor-agnostic model handoffs across GPT-4, Claude, and Gemini, preventing vendor lock-in.

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Benefits

Remote Work Options

Relocation Assistance

Company Equity

Meal Benefits

Growth & Insights and Company News

Headcount

6 month growth

17%

1 year growth

17%

2 year growth

17%
Dedalus Labs
Jan 19th, 2026
Introducing Dedalus Auth

Introducing Dedalus Auth. Dedalus Auth (DAuth) is a multi-tenant authentication layer for MCP servers and marketplaces that protects user credentials and closes security gaps without requiring developers to become security experts. Introducing Dedalus Auth (DAuth). Today Dedalus Labs is excited to launch Dedalus Auth (DAuth), a new way to secure Model Context Protocol (MCP) servers and marketplaces. Its authentication architecture protects user credentials and solves long-standing security gaps in the MCP landscape. DAuth is designed specifically for MCP: it's multi-tenant, faithful to the MCP specs, and ensures that no one can see your secrets, not even Dedalus Labs. Existing auth implementations are underdeveloped and difficult for smaller developers to implement. API keys and raw secrets are still being passed around with limited protection, making them vulnerable to malicious servers that hijack user credentials. To build MCPs with production-grade security, developers need to spend weeks becoming security experts to build authentication and security infrastructure. Most don't bother. But Dedalus Labs believe you shouldn't have to compromise on security. That's why Dedalus Labs developed DAuth, so MCP creators don't have to reinvent auth infra, and users never have to hand secrets to strangers. The best thing about DAuth is that it is built in to its SDK, takes minutes to integrate, and doesn't require developers to be security experts. Security is the bottleneck for MCP adoption. The biggest barrier to deploying AI agents in production is trust. Recent high-profile security incidents have shown that MCP can be a vulnerable vector of attack for malicious actors. If Dedalus Labs is going to give agents the tools they need to be useful, their permissions must be handled accurately and securely. When Dedalus Labs started building its MCP marketplace, Dedalus Labs were disappointed by the state of MCP auth. MCP standardized around OAuth, but it doesn't support dynamically passing API keys, forcing existing MCP marketplaces to be OAuth-centric and single-tenant. In addition, the MCP specs don't specify how non-OAuth credentials should be handled. This is a problem because most MCP servers are non-OAuth, as many of the tools developers use are not authenticated by OAuth, like a search API or database credentials. For developers using those tools, MCP security becomes a chore. To do things the "right way," you need to create your own OAuth app for every tool. The easier route, storing raw credentials with the host, turns marketplaces into a single vector of attack: one malicious actor can collect thousands of secrets. No existing MCP authentication solution serves its users security needs. No one else seems to be working on one that will. So Dedalus Labs built the missing baseline: secure, multi-tenant auth that doesn't depend on every tool being OAuth. At the core of its authentication layer is a multi-tenant infrastructure. Single-tenant authentication means that every deployed MCP server needs to deploy its own authentication layer. Multi-tenant authentication means servers using its SDK can authenticate with DAuth, serving as a single authentication layer for every MCP server Dedalus Labs host. Its unique architecture is zero-trust and host-blind, which means Dedalus never sees raw API keys or access tokens. Here's what that looks like in practice: * The Dedalus SDK performs client-side encryption on your credentials, protecting secrets before they leave your device. * Whenever the SDK needs permission to do something, Dedalus Labs initiate a secure exchange, calling its open-source auth server to validate access. * When a user request reaches your MCP server, the server acts as a standard OAuth 2.1 Resource Server. Access is verified without ever touching the credential. * Once the MCP server validates a request, Dedalus Labs send it to The Enclave, a network-less hardware-secured enclave written in Rust. * Within this network-less Enclave, your credentials are checked for milliseconds before being zeroed from memory. * Then, the request is encrypted before being sent downstream, without ever revealing the secret to Dedalus or your MCP server. The Enclave is a digital Fort Knox, a network-less fortress built in Rust that neither remote hackers or Dedalus can see your secrets. Best of all, this works across all auth cases. This lets Dedalus Labs offer much stronger security guarantees than any existing marketplace or solution. With DAuth, Dedalus Labs is proud to offer the only secure and multi-tenant marketplace to date. If you're interested in learning more about its system, check out its technical blog post explaining how Dedalus Labs built it. Now that Dedalus Labs can trust agents, what's next? The best part about DAuth is that you no longer need to be a security expert to build production-grade MCP-powered agents. DAuth is built into the Dedalus SDK. Rather than implementing OAuth flows that change with each tool, developers define an Intent (e.g., slack_read) that ensures permissions can't be hijacked by malicious actors. This intent-based system can be implemented in a few lines of code, removing the burden of security from the developer. For users, this means they can trust MCPs made by anyone using the DAuth framework the same way they would trust an MCP from a big name like Google. DAuth opens up a new world of possibilities, where trust is a default on its platform. Dedalus Labs believe MCP won't matter in production until auth stops being optional and secrets are no longer out in the open. Security is the key to creating a robust, community-driven agent economy, where trust is essential to both creators and end users. Dedalus Labs is rolling out updated docs and example use cases to show you how to use DAuth to build useful agents in the real world. If MCP is going to power real-world agents, security can't be optional. When you build or run on Dedalus, you're opting into a standard you can trust. If you want to try auth today: * Build with Dedalus Labs Authentication Layer for FREE by deploying an MCP with its SDK. Free credits available until Jan. 27. * More use cases coming soon.

Dedalus Labs
Oct 19th, 2025
We raised $11M to redefine how developers build AI agents

Dedalus Labs raised $11M in seed funding to help developers build complex agents across any model and tool in 5 lines of code, led by Kindred Ventures and Saga Ventures.