Staff Software Engineer, GCS Object Context and Search
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- 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
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of software development experience.
- 3 years of experience leading the technical direction, design, and roadmap for systems or product areas.
- 3 years of experience mentoring, coaching, and growing software engineers.
- 3 years of experience with systems programming in C++.
- 3 years of experience with stateful distributed systems, search infrastructure, or database internals.
Preferred qualifications:
- Experience architecting, scaling, and maintaining stateful Distributed Systems, search infrastructure, vector databases, or high-performance embedding storage.
- Expertise in C++ systems programming, with a strong focus on low-level performance optimization and modern C++ best practices.
- Proven track record of designing and establishing diagnostic frameworks, testing infrastructure, or systems instrumentation that guarantee long-term performance and reliability.
- A customer-centric approach to engineering, with a history of leading data-driven initiatives to analyze and optimize system efficiency, network throughput, or search relevance.
About the job
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.We are seeking a Staff Software Engineer to join our Google Cloud Storage Object Context and Search team.
In this role, you will lead the design and development of critical capabilities that enable customers to build semantic storage and search solutions on Google Customer Solutions (GCS). You will play a key role in shaping the reliability, scalability, performance, and relevance of our systems, helping guide the technical direction of a critical infrastructure pillar within Google Cloud Platform. You will join a supportive, highly collaborative environment, where you will partner with executive technical leadership to advocate a positive engineering culture that makes solving complex systems issues rewarding.
US: $207000 - $301000 (USD) + 20% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead the design, architecture, and optimization of key components of GCS's vector database and semantic search engines (C++), focusing on high-performance storage and low-latency retrieval at planet scale.
- Own the technical roadmap and execution strategy for major sub-systems, collaborating closely with executive technical leadership to align with the overall project and GCS goals.
- Partner with adjacent infrastructure teams to design and build faster, more reliable, and highly scalable systems that operate within GCS's strict resource and throughput constraints.
- Establish engineering excellence standards for testing, diagnostics, and observability, ensuring the system is performant, reliable, and easy to debug in production.
- Identify and address systemic engineering bottlenecks, generalizing common patterns to improve development velocity and system health across the team.
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