The posting
In most instances, this position requires in-person interviews as part of the hiring process.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- 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
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; Austin, TX, USA; Kirkland, WA, USA; Seattle, WA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with Large Language Models (LLMs) and Generative AI concepts (e.g., prompt engineering, retrieval-augmented generation (RAG).
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
Preferred qualifications:
- Experience productionalizing advanced LLM architectures (e.g., agentic workflows, function calling, tool use, prompt chaining, or fine-tuning techniques).
- Experience building automated LLM evaluation suites, benchmarking pipelines, and continuous regression testing for probabilistic model outputs.
- Experience working with unstructured text data, document processing pipelines, and vector databases in high-stakes domains (e.g., Legal, Regulatory, Compliance, or Trust and Safety).
- Experience applying software and AI/ML solutions to domains such as Governance, Risk, and Compliance (GRC), Security, or Privacy.
- Demonstrated ability to design robust error handling, fallbacks, and monitoring/alerting infrastructure for production services.
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.
Global Affairs is composed of teams that are experts in technology issues that lie at the intersection of public policy, regulation, compliance, user trust and safety, and legal.
As a part of the Global Affairs, you will play a critical role in Google's priorities, including regulatory life-cycle work, external engagement with key stakeholders worldwide, efforts to ensure trustworthy products, and support of the incredible opportunities opening up in artificial intelligence and beyond. You will have an important role to play for our company, its partners, and the people who use our products.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write clean, testable, and resilient production code in Python, C++, or Java, implement automated integration, stress, and regression testing for Large Language Model (LLM) pipelines, proactively identify and pay down technical debt.
- Deliver complete, robust software components and services that productionalize Data Science prototypes, LLM pipelines, and AI workflows with minimal supervision.
- Implement orchestration logic, context window management, structured output parsing, and API integrations connecting foundational LLMs to backend systems and frontend interfaces.
- Build and maintain automated evaluation pipelines (LLM-as-a-judge, benchmark suites, deterministic unit tests) to monitor hallucination rates, output quality, and inference latency.
- Partner effectively with Data Scientists, Web Solutions Engineers, and Technical Program Managers to clarify requirements, manage component dependencies, and unblock execution.
