Product Solutions Engineer

About the role

You will own 5-15 active model lab relationships as the day-to-day point of contact for the most demanding AI labs in the world. You will partner directly with researchers and product teams to integrate models, run evals, and deliver high-quality results that move the needle on model behavior. You will drive consistent delivery across onboarding, data + product releases, co-launches, and unblock unexpected issues fast with clear ownership. You will be the "owner" of a key process improvement or automation such as model onboarding flow, customer data insights, or delivery tooling that materially changes how Arena operates. You will translate customer feedback and research direction into concrete product ideas and engineering work that directly shapes the platform. You will work across the stack to ship pragmatic solutions that push the frontier for our customers without waiting for a perfect spec. You will help expand strategic accounts through trust, execution, and sharp technical judgment that turns early pilots into long-term partnerships.

Key facts

What you'll do

• Orchestrate day-to-day engagement with 5-15 active model lab relationships serving as the primary interface for integrations, evals, and strategic initiatives.
• Partner directly with research and product teams to integrate models, design and run evals, and deliver rigorous, high-quality results that inform product decisions.
• Drive consistent delivery across onboarding, data and product releases, co-launches, and incident response to unblock unexpected issues with speed and clarity.
• Own a key process improvement or automation such as model onboarding flow, customer data insights, or delivery tooling that scales across the organization.
• Translate nuanced customer feedback and emerging research direction into concrete product ideas and engineering work prioritized against business impact.
• Work across the full stack to ship pragmatic solutions that push the frontier for customers, balancing speed, quality, and long-term maintainability.
• Expand strategic accounts by building trust, demonstrating execution excellence, and applying sharp technical judgment to solve high-stakes problems.
• Collaborate with cross-functional stakeholders to align on goals, surface risks early, and ensure commitments are met with transparent communication.
• Maintain deep context on model lab roadmaps and use that insight to anticipate needs and propose proactive solutions before they become critical.
• Champion data-driven decision making by defining success metrics, running experiments, and iterating based on observed outcomes in real workflows.
• Contribute to the broader product and research discourse by documenting patterns, sharing findings, and influencing the long-term vision for the platform.
• Operate comfortably in ambiguity, balancing competing priorities while maintaining a high standard of quality and accountability.
• Represent Arena Intelligence in external interactions, ensuring that communications are clear, accurate, and aligned with customer and company goals.
• Continuously refine your own playbook for customer engagement, drawing on feedback to improve processes, tools, and outcomes over time.

Requirements

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design.
• Production experience in TypeScript and modern web frameworks that demonstrates shipped user-facing features.
• Hands-on experience integrating LLM provider APIs, including handling streaming responses and managing state across long-running interactions.
• Comfort moving across frontend and backend - you are willing to dig in wherever the problem lives and ship fixes end-to-end.
• Familiarity with cloud infrastructure and CI/CD workflows that underpin reliable, scalable deployments.
• Strong problem-solving instincts and the ability to operate productively in ambiguity without sacrificing rigor or clarity.
• Clear, concise communication skills that enable you to explain complex technical ideas to both engineers and non-technical stakeholders.
• A customer-first mindset and a genuine desire to work closely with multiple stakeholders to understand needs and deliver outcomes.
• Commitment to following processes and tooling while also identifying opportunities to improve them in partnership with the team.
• Willingness to work within the constraints of current systems while thinking critically about where automation and abstraction can have outsized impact.
• Alignment with Arena Intelligence values of truth, craftsmanship, curiosity, and impact over hierarchy.
• Ability to manage multiple active relationships and priorities without compromising on quality or responsiveness.
• Willingness to learn deeply about AI model evaluation, real-world workflows, and the constraints of production environments.
• Comfort presenting findings and recommendations to both technical and executive audiences with clarity and precision.

Nice to have

• Preferred items from the source are not specified; there are no explicit nice-to-have qualifications listed.

Practical notes

• Hours: Full-time during standard business hours.
• Travel: None stated.
• Visa: None stated.
• Deadlines: None stated.