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Staff Software Quality Engineer in San Francisco

94 active opportunities · Updated October 2026

Explore current staff software quality engineer jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.

SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $252K/yr

Quick readStrong listing-quality and freshness signals

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

AWSAzureGCPDocker
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $252K/yr

Quick readStrong listing-quality and freshness signals

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

MongoDBRedisAWSKubernetes
L
📍 San Francisco, Canada· Full-time
✓ High-confidence listingCompany trend -74.4%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Lyft Business organization builds the platform that lets organizations move the people they depend on employees, clients, and customers. From the foundational mechanics of a company funding and provisioning a ride to the tailored workflows that get an employee to a client meeting or home after a late shift, we sweat the small stuff to make Lyft the transportation solution businesses build their programs on. As a Staff Software Engineer on the Lyft Business Team, you will act as a critical technical leader, taking holistic ownership of complex systems that span the rider experience, the administrator experience, and the enterprise integrations behind them — defining strategic roadmaps, driving cross-functional alignment, and driving engineering excellence to improve how organizations move their people. Responsibilities: Shape the long-term architecture for systems, taking accountability for both short-term functionality and long-term health Translate high-level business goals into actionable engineering projects. Own the technical roadmap from conception to delivery, managing cross-team dependencies and mitigating risks Champion improvements in system, observability, performance, and tech debt reduction, extending your influence beyond your immediate team Establish best practices for deployment, alerting, and on-call health. Take holistic ownership of the platform's stability, tracking down issues root causes and building preventive safeguards for your immediate scope and beyond. Drive alignment across product, design, and operations. Proactively resolve bottlenecks and make decisive trade-offs to protect system architecture from competing organizational priorities Mentor and level up the engineers around you. Delegate stretch opportunities, lead cross-team reviews, and foster a culture of s

SQLAWSAzureGCP
A
📍 San Francisco, Canada· Full-time
✓ High-confidence listingCompany trend -87.1%

From $212K/yr

Quick readStrong listing-quality and freshness signals

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. Many of the initiatives you’l

Machine LearningAIRust
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