Software Engineer, Agentic AI, Trust and Safety

Staff Software Engineer, Agentic AI, Trust and Safety

Location:

Kirkland, WA, USA

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience with designing and implementing large-scale distributed systems.
• 5 years of experience with machine learning (ML) infrastructure or another ML field.
• Experience with architectural ownership for distributed systems or infrastructure components.
• Experience building and deploying agentic AI systems.

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• Experience managing rapid technical iteration, 0->1 innovation, and managing deep technical ambiguity across multiple engineering organizations.
• Experience defining organization-wide technical strategies, establishing engineering best practices, and mentoring Executive Engineers and Tech Leads.
• Background in Trust and Safety, content moderation, security, or anti-abuse engineering at a global scale, managing billions of daily events or real-time streaming data.
• Strong technical communication skills, with a proven ability to translate complex architectural trade-offs and AI capabilities into recommendations for cross-functional executives.

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile;

the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will steer a high-performing engineering organization. You will architect fault-tolerant, and horizontally scalable solutions across the entire technical stack, ensuring user protection at Google scale.

You will grow in ambiguity, resolving cross-system friction and managing systemic risk across complex distributed networks. You will act as a massive multiplier: defining engineering standards, mentoring tech leads across the organization, enforcing operational excellence and driving cross-functional technical execution.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $301000 (USD) + 20% bonus target + bonus + equity + benefits.

Learn more about benefits at Google.

• Define, advocate, and execute the overarching Trust and Safety technology roadmap, architecting next-generation AI/ML systems and highly reliable distributed infrastructure to automate and scale global user protection.
• Oversee the integration of high-availability, low-latency production systems with stringent Service Level Objective (SLO) guarantees, driving excellence across system bottlenecks, data consistency, capacity planning, and cost-efficiency.
• Steer critical, multi-team technical initiatives from initial abstract discovery through to large-scale deployment, translating…