Who is Litmus

Litmus is building the data foundation that powers industrial AI.

AI doesn’t work without real-world, contextualized data - Litmus makes that data usable. As AI adoption accelerates, most industrial environments still can’t access or use their operational data. We solve that gap.

We’re a growth-stage software company helping manufacturers access, structure, and use real-time data from machines, systems, and sensors at the edge. Our platform sits at the intersection of edge computing, AI, and industrial operations, enabling some of the world’s largest companies to run operations in real time, reduce downtime, and optimize production.

Backed by leading investors and trusted by global manufacturers and partners like Google, Microsoft, Dell, Oracle, and Mitsubishi, Litmus is powering the shift toward software-defined manufacturing.

Why join Litmus

Build the infrastructure that makes industrial AI possible

AI is moving beyond the cloud and into the physical world. At Litmus, you’ll build the infrastructure that enables real-time data to power AI and machine learning systems in production environments.

Work on problems where software meets the real world

Most AI systems fail without access to real-world data. You’ll build the layer that makes them viable in production. We solve challenges at the intersection of distributed systems, real-time data, and industrial constraints — where reliability, scale, and performance are non-negotiable.

Have real impact, fast

You’ll work on systems used by real customers in production, with direct impact on product and company trajectory. As a scaling company, we move quickly. You’ll have ownership, visibility, and the ability to shape both product and company as we scale.

Join a high-performance team

We’re building a team that holds a high bar and pushes each other to improve. You’ll work alongside experienced operators, engineers, and leaders who have done this before and are building again at scale. We hire people who take ownership, move quickly, and care about outcomes. No passengers.

Our culture

At Litmus, the team is collaborative, curious, and low ego. People are scrappy, take ownership, and look for ways to make an impact. We value empathy just as much as execution, whether that’s in how we build, how we communicate, or how we support each other.

We’re a growing company, so things move quickly and not everything is perfectly defined. If you enjoy figuring things out, working closely with others, and making steady progress, you’ll do well here.

What You'll Do

• Own end-to-end documentation for Litmus's AI/ML capabilities — edge inferencing, anomaly detection, predictive maintenance, model configuration, and limitations — across Litmus Edge and Litmus Edge Manager.

• Translate complex AI/ML and industrial-IoT concepts into clear, accurate content for plant engineers, IT/OT admins, and developers.

• Design and run AI-assisted documentation workflows: LLM-assisted drafting, automated accuracy/consistency checks, and docs-as-code pipelines.

• Partner directly with product managers and ML/data engineers to document model behavior, APIs, and configuration before and at release.

• Set authoring standards and prompt guidelines for how the writing team uses AI tools, and mentor other writers on adoption.

• Maintain information architecture across the help center, in-product help, API reference, and release notes.

• Validate documentation against actual product behavior through hands-on testing, not just spec review.

What You Bring

• 5+ years of technical writing experience, ideally in B2B, industrial, or IoT software.

• Demonstrated experience documenting AI/ML or data-driven product features.

• Hands-on production experience using AI writing tools (e.g., Claude, ChatGPT, Copilot) to draft, edit, or QA documentation — not just occasional use.

• Comfort working docs-as-code: Markdown, Git, static site generators.

• Strong ability to interview engineers and PMs and turn technical/AI concepts into clear content independently.

• A portfolio demonstrating both technical depth and clarity of writing.

Nice to Have/Preferred Skills

• Experience with structured authoring (DITA) or API documentation tooling (Swagger/OpenAPI).

• Working literacy in ML/data science concepts (model training, inference, drift).

• Experience building internal AI tooling or copilots for a documentation team.

• Background in industrial IoT, manufacturing, or OT/IT convergence.