Hasbro
Principal Software Engineer
$173K–$259K
Renton, Washington, United States · Principal · Full-time · Posted Oct 9, 2026
- Experience
- Over 10 years of full-stack software engineering; at least 3 years in a Tech Lead, Staff, or Principal role.
- Education
- Bachelor’s degree or equivalent experience in Computer Science, Information Technology, or comparable work experience.
About the job
Leads the end-to-end development and production improvement of digital products using agentic AI, setting technical direction and driving data-informed business outcomes.
What you'll do
- Guide product concepts from problem definition through prototyping, launch, and iteration based on usage data.
- Build and ship production agentic AI systems, prompts, analyses, and supporting services; contribute to shared harness engineering patterns.
- Set engineering standards and technical direction, while mentoring engineers and contributing to hiring and technical interviews.
What they ask for
- Direct experience developing, deploying, and improving agentic AI systems in real-world production settings.
- Over 10 years of full-stack software engineering experience, including at least 3 years in a Tech Lead, Staff, or Principal role guiding technical direction.
- Modern JavaScript / TypeScript and at least one of Go, Python, or C#; production coding experience.
- Bachelor’s degree or equivalent experience; strong systems and infrastructure experience, including AWS at scale, CI/CD, PostgreSQL, APIs, test automation, observability, and reliability.
Nice to have
- Experience with platform or horizontal services, Product Lifecycle Management (PLM), or a tri-lead engineering model.
- Experience with Kubernetes, Akamai, Terraform, or equivalent infrastructure-as-code tooling; familiarity with Magic: The Gathering, Dungeons & Dragons, or tabletop gaming.
Pay
$172,600 — $259,000 USD (base salary)
Tools
JavaScript, TypeScript, Go, Python, C#, AWS, PostgreSQL, Kubernetes
AI focus
Hands-on development, deployment, evaluation, and production iteration of agentic AI systems; work includes prompts, tools, LLMs, agents, Skills, MCP, evaluation frameworks, guardrails, and consideration of cost, latency, determinism, and reliability.
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