We take play seriously. We’re looking for curious adventurers ready to find their party, fueled by imagination and drive to build what’s never been built before. At Hasbro and Wizards of the Coast, you’ll collaborate with passionate teams to reimagine our iconic brands and create experiences that spark joy, connection, and community through the magic of play. This is your chance to shape legendary play that lasts a lifetime.

Job Overview

The Digital Innovations Team (DigIT) is changing how Wizards develops, delivers, and manages the digital systems behind our games — for players, retailers, and the studios that develop our worlds. We are seeking a Principal Software Engineer who can guide product ideas through every stage with agentic AI — from defining the problem with business partners, to developing the system, to deploying it in production, and then improving it based on actual data.

This role is hands-on. We need a creator who builds and ships with agentic AI. Someone who has directly shipped product to production by agentic AI, can provide the code and performance assessments, and can discuss in detail what was successful, what did not succeed, and what they would do differently. If you have built and shipped with agentic AI and want to keep building, we'd love to hear from you.

You will be responsible for the technical direction of an initiative and the related product surface area, direct tech direction and product direction with or without Product Manager (PM) support. You are answerable for what the team delivers, how quickly it adapts, and the business outcomes that result.

You will build products with agentic AI as your default approach, using the harness engineering and guardrails the team has developed and helping evolve them alongside peers. Your primary focus is shipping product, and you bring production-based judgment about evaluations, guardrails, cost, latency, determinism, and delivering AI products responsibly at scale.

Location and Work Arrangement

This role is based at our Renton, Washington office and follows a hybrid schedule designed to support in-person collaboration. Employees are expected to work onsite on Tuesdays, Wednesdays, and Thursdays, with the flexibility to work remotely or onsite on Mondays and Fridays.

What You'll Do

Guide product concepts through the entire process with agentic AI. Starting from outlining the problem alongside product and business collaborators, moving to prototype development, to a data-informed launch, and then refining based on actual usage data. You are responsible for the full journey, not only a segment of it.
Build, hands-on with agentic AI. Keep close to the code. Deliver production-quality agent systems, analyses, prompts, and supporting services on your own. Set the standard for agentic AI development through delivered, working results rather than discussion.
Direct the build process through data-driven insights. Lead product ideas as testable hypotheses. Start tracking early and confirm success criteria before coding begins, with or without PM support. Base decisions on actual data concerning what to prioritize, change, or remove. Ensure the feedback loop is as short as feasible.
Contribute to the department's agentic AI harness engineering alongside peers. Apply, stress-test, and improve shared patterns — LLMs, agents, Skills, Model Context Protocol (MCP), eval frameworks, guardrails — through real production use. Bring back what works and what doesn't from the field.
Raise the engineering bar on architecture, code review, test strategy, observability, evals, and incident quality. Treat engineering excellence as a baseline expectation, not an optional initiative.
Provide technical leadership and influence both people and product decisions. Make your EM and PM more effective in their roles.
Contribute to the hiring bar. Lead technical interviews, calibrate the AI-capability signal in our hiring loop, and mentor the next layer of senior and staff engineers.

What You'll Bring

Direct experience creating agentic AI systems. You have developed, deployed, and improved agentic systems in real-world settings, beyond demos or proofs of concept. You can describe the code you authored, the tests you designed, the prompt and tool usage changes you made, the cost and latency considerations you evaluated, the failure types you managed, and the metrics you used to choose the next release. Interviews will involve a hands-on agentic AI task.