AI Solutions Engineer, East

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 , Uber, Siemens, and Pepsi Co leverage Arize to deliver AI that works.

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, ride sharing marketplaces, ad tech and much more.

• Work closely with some of the most sophisticated ML/GenAI teams in the world.
• Act as a trusted advisor to our customers, 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 the pre‑sales engineering team to gather client goals and KPIs.
• Partner with product and engineering teams to help drive the product roadmap.
• Spearhead new opportunities within existing accounts to help drive expansions.

While we are a remote‑first company, the nature of this role requires candidates to be based in the New York City metro area / EST time zone.

Previous experience working as a Data Scientist, Machine Learning Engineer, or 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 Tensor Flow, PyTorch or Scikit‑learn.

Knowledge of LLM / Agentic frameworks such as Llamaindex, Lang Graph, 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.

• 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 additional support for mental and wellness.

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.

Our mission is to make the world’s AI work—and work for people.

Learn more about what we're doing here:  

• 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.