Staff Software Engineer — GenAI & Scalable Systems

Google Inc.

Greater London

Hybrid

GBP 140,000 - 210,000

Full time

13 days ago

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Job summary

Google Inc. is seeking highly skilled software engineers to join our team in London, tackling large-scale systems, AI, and data-driven challenges. You will own outcomes, influence stakeholders, and work across full-stack architectures.

Ideal candidates bring 8+ years of experience in C++, Java, Kotlin, and Typescript, with ML familiarity and a track record of shipping product features at scale.

Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of full-stack software development in C++, Java, Kotlin and Typescript.
  • 3 years in frontend frameworks, full-stack development, or API development.
  • 1 year in software design, architecture, and ML.
  • 1 year in agentic coding.

Responsibilities

  • Partner with Google DeepMind to translate GenAI research into products.
  • Architect and build new products from the ground up, moving prototypes to production.
  • Design and implement agentic systems and multi-step AI prompts to solve complex, open-ended scientific tasks using the latest LLM reasoning advancements.
  • Establish frameworks and metrics to measure model performance, driving continuous quality improvements and model fine-tuning for specific scientific use cases.
  • Work closely with Product Managers and UX partners to discover user needs and iterate on features that genuinely delight the scientific community.

Skills

Full-stack
C++
Java
Kotlin
Typescript
Frontend frameworks

Education

Bachelor's degree
Master's or PhD

Tools

GCP
APIs

Job description

Google Inc. is seeking highly skilled software engineers to join our team in London, tackling large-scale systems, AI, and data-driven challenges. You will own outcomes, influence stakeholders, and work across full-stack architectures.

Ideal candidates bring 8+ years of experience in C++, Java, Kotlin, and Typescript, with ML familiarity and a track record of shipping product features at scale.

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