AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence.
We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.
At Arize AI, we’re building the category-defining platform for AI observability, evaluation, and reliability.
AI is moving fast, but most teams are still flying blind once their agents hit production. We help teams understand how their agents behave, evaluate performance, and improve over time.
Our mission is simple: build the feedback loop that helps teams ship agents that actually work in the real world.
The RoleWe’re looking for someone who thinks like a marketer and acts like a journalist to bring clarity to how modern AI systems are built and improved. This is a technical content role. You’ll work directly with engineers, researchers, and product teams to understand how AI systems actually work. Then, you’ll turn that into content that helps other engineers build, evaluate, and ship with confidence.
This role isn’t about summarizing ideas. It’s about extracting real workflows, pressure-testing them, and publishing content that’s immediately useful. You should already have a strong technical foundation. You’ll be expected to engage deeply with topics like evaluation, observability, agents, and LLM systems — and translate them without losing precision.
You’ll operate as both a strategist and a high-output individual contributor in a role where what you create ships quickly and gets used.
What You’ll DoWrite Technical Content That Engineers Actually Use- Produce high-quality technical content: deep dives, guides, tutorials, and system-level explainers
- Break down complex topics (evals, agents, observability, prompt iteration) into clear, actionable workflows
- Focus on content that helps developers do something, not just understand something
- Work directly with engineers, researchers, and customers to extract insights and real-world workflows
- Ask strong technical questions and push for clarity where things are vague
- Turn conversations into structured, high-signal content
- Identify gaps in what developers are struggling with
- Prioritize and ship content that addresses those gaps
- Balance long-term narrative with immediate, high-impact output
- Use AI tools to accelerate writing, editing, and research
- Build systems that increase content velocity without lowering quality
- Treat content as a compounding system, not a one-off deliverable
- Partner with Product, DevRel, and Marketing to ensure accuracy and relevance
- Align content with what’s actually shipping
- Contribute to how Arize explains AI engineering as a discipline
You must be comfortable writing about:
- Software engineering
- AI/LLM application development
- Developer workflows
This is not a role for someone learning the space from the outside.
Content & Communication- Strong writing and editing skills — you can explain complex systems clearly without oversimplifying
- Experience creating technical content (blogs, guides, docs, or similar)
- Ability to interview SMEs and turn conversations into structured, useful content
- You can think strategically and execute tactically
- You ship consistently and take ownership of output
- You’re comfortable working in a fast-moving, high-ownership environment
- You actively use AI tools in your day-to-day work
- You think in terms of leverage, iteration, and systems
- You’re interested in how AI changes how content gets created
- Experience building or working with LLM-based systems (RAG, agents, eval frameworks)
- Experience writing tutorials or developer documentation
- Background spanning both technical work and editorial/journalism
AI systems are getting more complex, and harder to reason about.
The limiting factor for most teams isn’t access to models. It’s understanding:
- what to evaluate
- how systems fail
- how to improve them
Your job is to make that legible for engineers who are actively building.
Why Arize- Work at the center of the AI engineering ecosystem
- Help define how AI systems are evaluated and improved
- Build content that reaches and helps real practitioners
- High ownership, fast iteration, and direct impact
Salary Range $160,000-$190,000 plus a generous equity package depending on experience
Arize’s mission is to make the world’s AI work—and work for people.
Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale.
Learn more about what we're doing here:
https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/
https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/
Diversity & Inclusion @ Arize
Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture
- Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI
- Culturally conscious events such as LGBTQ trivia during pride month
- We have an active Lady Arizers subgroup
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