Backend Engineer

Reposted 2 Days Ago
San Francisco, CA, USA
In-Office
Mid level
Artificial Intelligence • Software
The Role
As a Backend Engineer, you'll develop infrastructure for AI agents, design APIs, and ensure reliable, scalable systems while collaborating across teams.
Summary Generated by Built In
About Navier AI

Navier AI is building the first autonomous engineering agents. AI systems that can design, simulate, and optimize complex products to achieve breakthrough levels of performance. Our mission is to enable engineers to move beyond today’s slow, manual design cycles by providing agents that reason about physics, explore design trade-offs, and generate high-performance solutions across aerospace, automotive, and advanced manufacturing.

We’re backed by top-tier investors and work directly with industry leaders to deploy AI-native tools that go far beyond today’s design automation.

Role Overview

We’re hiring a Backend Engineer to help build the infrastructure behind our autonomous engineering agents. You’ll work across model serving, simulation orchestration, multi-agent coordination, and developer-facing APIs. This role is critical to delivering fast, reliable, and scalable systems that engineers can trust in production design environments.

Responsibilities
  • Own core backend systems for serving AI agents and managing their compute, data, and model coordination
  • Design and implement APIs that expose agent functionality—simulation control, CAD operations, optimization workflows—to internal tools and customer integrations
  • Build secure, scalable infrastructure for multi-agent orchestration, including support for containerized workloads, caching, and distributed compute
  • Collaborate closely with ML, frontend, and simulation engineers to create a cohesive, performant product experience
  • Integrate external tools such as CAD software, simulation backends (e.g., OpenFOAM), and data stores into our pipeline
  • Support agent development workflows, including tooling for versioning, introspection, and reproducibility
  • Contribute to infrastructure decisions that will shape the technical foundation of our platform as it scales
  • Engage directly with early customers to support integration, identify infrastructure needs, and gather feedback
Qualifications

Required:

  • Strong backend engineering skills in Python or similar languages
  • Experience designing and maintaining production APIs
  • Familiarity with containerized development and deployment (e.g., Docker, Kubernetes)
  • Comfort building infrastructure that supports AI/ML systems or computational workflows
  • Strong systems thinking and ability to reason across compute, data, and model interactions
  • Experience in fast-paced environments where end-to-end ownership is expected
  • Excellent communication and collaboration skills

Preferred:

  • Expertise in FastAPI
  • Experience integrating with scientific software (e.g., CAD, FEA, CFD tools)
  • Exposure to agent frameworks, workflow orchestration, or distributed systems
  • Familiarity with model serving (e.g., TorchServe, Triton) or simulation backends
  • Interest in physics, geometry, or real-world engineering applications
  • Prior experience building developer tools or working in high-trust customer-facing roles
Why This Role Matters

We’re not just building software—we’re building the future of engineering itself. As a backend engineer at Navier, you’ll architect the systems that allow our AI agents to reason, simulate, and design like expert engineers. Your work will directly impact how rockets, cars, aircraft, and next-gen hardware are conceived and built.

What We Offer
  • Competitive compensation, including salary and equity
  • Direct exposure to high-impact technical problems in aerospace, automotive, and advanced manufacturing
  • Opportunity to help define a new category of engineering software

Skills Required

  • Strong backend engineering skills in Python or similar languages
  • Experience designing and maintaining production APIs
  • Familiarity with containerized development and deployment (e.g., Docker, Kubernetes)
  • Comfort building infrastructure that supports AI/ML systems or computational workflows
  • Strong systems thinking and ability to reason across compute, data, and model interactions
  • Experience in fast-paced environments where end-to-end ownership is expected
  • Excellent communication and collaboration skills
  • Expertise in FastAPI
  • Experience integrating with scientific software (e.g., CAD, FEA, CFD tools)
  • Exposure to agent frameworks, workflow orchestration, or distributed systems
  • Familiarity with model serving (e.g., TorchServe, Triton) or simulation backends
  • Interest in physics, geometry, or real-world engineering applications
  • Prior experience building developer tools or working in high-trust customer-facing roles
Am I A Good Fit?
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The Company
7 Employees

What We Do

Making CFD 1000x faster

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