About Arize

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.

The Team

Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more.

We are looking for a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize.

What You’ll Do

Work closely with some of the most sophisticated ML / GenAI teams in the world.
- You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.
Advise on GenAI and ML best practices
Give ML and LLM product demos to technical and business stakeholders
Run strategic business reviews for customers in partnership with our sales team
Interface with our pre-sales engineering team to gather client goals and KPI’s.
Partner with our product and engineering teams to help drive the product roadmap
Spearhead new opportunities within existing accounts to help drive expansions.

What We’re Looking For

Note: Even if you do not check every single box, we still encourage you to apply!

Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
Comfortable working in public Cloud environments (AWS, Azure, GCP)
Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
Understanding of GenAI concepts and application evaluation + development lifecycle
Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
Strong Communication Skills - Ability to simplify complex, technical concepts.
A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

Bonus Points, But Not Required

Previous engineering experience in:
- Data Science
- MLOps
- ML Frameworks
- LLM / Agentic frameworks
Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
Prior experience working with applications deployed with Kubernetes
Prior experience demoing technical products to both business and technical audiences

The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.

While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.

More About Arize

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