AI Solutions Engineer

The Opportunity

AI is rapidly transforming the world, from developing human-level intelligence to enhancing voice assistants and enabling large-scale genetic marker analysis. AI is increasingly integrated into various aspects of our daily lives.

Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production.

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 who 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 organization. You’ll be the trusted technical advisor for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions, often 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.
• Act as a trusted advisor to our customers while 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 KPIs.
• 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 Services roles.
• Prior experience working with applications deployed with Kubernetes.
• Prior experience demoing technical products to both business and technical audiences.

Compensation

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...