Senior Software Engineer, Context Engineering, Fuchsia

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience with software development in either Python or Go

programming languages.

• 3 years of experience testing, maintaining, or launching software products,

and 1 year of experience with software design and architecture.

• 3 years of experience with developing large-scale infrastructure, distributed

systems or networks, or experience with compute technologies, storage or

hardware architecture.

PREFERRED QUALIFICATIONS:

• Master's degree or PhD in Computer Science or related technical field.

• 5 years of experience with data structures and algorithms.
• Experience developing, deploying, or fine-tuning agentic loops (e.g.,

tool-calling, multi-step planning, automated self-correction, or IDE coding

assistants like Jetski).

• Experience integrating automated bots, sidecars, or presubmit checks into

developer workflows across review platforms like Gerrit or Critique.

• Experience building quantitative evaluation harnesses to measure agent task

success, turn efficiency, token economics, or semantic drift.

• Familiarity with Abstract Syntax Trees (ASTs), static analysis, symbol

indexing, or building code-to-documentation knowledge graphs (e.g., mapping

symbols, FIDL/APIs, and manifests to guides).

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.

Context Engineering is the team responsible for building the context

infrastructure, document evaluation systems, and agent-ready documentation

platforms that power developer and Artificial Intelligence agent velocity across

our team and Fuchsia.

The Software Engineer (Context Engineer) role replaces traditional, manual

technical writing with scalable engineering automation under the charter of

“Task success through engineered context.” The role directly addresses Fuchsia’s

need for continuous context quality infrastructure delivering pre/post-commit

doc drift detection, the Fuchsia eXecutable (fx) knowledge graph code-to-docs

knowledge graph, and autonomous agent-driven doc remediation. By tying impact

directly to agent task success rates, reduced token bloat, and accelerated

time-to-first-edit, this role provides the foundational plumbing required to

sustain high-velocity agentic development across our team.

Fuchsia is a modern, open source operating system that is simple, secure,

updatable, and performant. It’s a general purpose OS, designed to power an

ecosystem of hardware and software, and provides core operating system functions

like system resource management, a driver framework, and software

abstractions.Individual pay is determined by factors including job-related

skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Write and test product or system development code.

• Participate in, or lead design reviews with peers and stakeholders to decide

amongst available technologies.

• Review code developed by other developers and provide feedback to ensure best

practices (e.g., style guidelines, checking code in, accuracy, testability,

and efficiency).

• Contribute to existing documentation or educational content and adapt content

based on product/program updates and user feedback.

• Build the software systems, automated pipelines, evaluation harnesses, and

knowledge graphs that transform documentation from static reference material

into dynamic, machine-actionable context that accelerates AI agents and human

developers across the Fuchsia ecosystem