Description

Position Overview:

As a Software Engineer III (AI), you'll build the AI infrastructure that runs natively on TrueNAS, turning a storage platform into an active participant in modern AI workflows, rather than a passive backend. This role typically suits engineers with a few years of varied software engineering experience, often around 3-5 years, and sits at the intersection of ZFS internals and applied ML infrastructure.

This is a remote position in the United States

Base Pay Range

The base pay range of this position is $140,000 to $160,000 USD annually.

Please note that the provided range reflects the pay spectrum for positions within the same job category as the one to which this position belongs. The final offer will consider various factors, such as location, education, and prior experience, to ensure a comprehensive and fair compensation assessment.

TrueNAS offers a comprehensive package of benefits including health, dental, vision, disability, and life insurance, paid time-off, 401(k), health and flexible spending accounts, stock purchase plan and more.

Expected Posting Timelines

This position will be open for a minimum of 5 days, a maximum of 90 days.

The Day-to-Day

The focus of this role will be in the development and optimization of critical capabilities that may include:

• On-array vectorization pipelines. Design and implement the systems that generate embeddings for data living on TrueNAS - including per-file sidecar generation driven by filesystem events and snapshot-time index compilation.
• GPU-accelerated inference. Build out the inference path using cuVS/CAGRA and similar libraries, targeting NVIDIA L4/A2-class GPUs in appliance form factors. You'll make decisions about model selection, quantization tradeoffs, and how inference workloads coexist with storage workloads on the same hardware.
• AIOps. Develop anomaly detection, predictive maintenance, and log analysis systems that consume the telemetry TrueNAS already produces. The goal is fleet-scale insight that's actually useful to operators, not dashboards full of noise.
• MCP and adjacent integrations. Extend our MCP surface so TrueNAS systems are first-class citizens in agent-driven workflows - both as data sources and as systems agents can operate on.

This prepares you for Software Engineer IV (AI), broadening your scope and influence over the AI platform direction.

Education and Experience

What we're looking for:

• Strong backend engineering fundamentals. You're comfortable in Go, Python, or C and can pick up the others. You've shipped systems that handle real load.
• Hands-on experience with vector search, embedding models, or RAG pipelines in production. You understand the difference between a demo and something that holds up under scale.
• Familiarity with GPU programming or GPU-accelerated libraries (CUDA, cuVS, DALI, TensorRT, or equivalents).
• Comfort working close to the storage and filesystem layer. ZFS experience is a strong plus; if not ZFS, then equivalent depth in another filesystem.
• Experience with Agentic Engineering. You should have a solid understanding of how to use AI-first development workflows for most common engineering disciplines.

Strong plus:

• Background in time-series anomaly detection or ML-driven observability.
• Contributions to open-source storage, ML infrastructure, or MCP-related projects.
• Experience with model quantization (4-bit, BitNet) and on-device inference constraints.
• An undergraduate or advanced degree in Computer Science, Computer Engineering, or a related discipline is expected, with comparable work experience as an alternative.

In addition to your education and experience, the following skills and abilities are desired in the ideal candidate for this position: Collaboration, Communication, Personal Effectiveness, Delivery, Problem Solving, Strategic Thinking, and Analytical Thinking.