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Sauce Labs

Automated cross-browser web and mobile testing

AI Architect

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeGurugram, Haryana, IndiaNo salary listed

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • At least 7 years of experience in software development and architecture of production-grade systems.
  • Proven experience designing, building, and deploying large-scale AI and machine learning systems and platforms in production.
  • Deep hands-on experience with Google Cloud Platform services relevant to AI and machine learning, such as Vertex AI, BigQuery, Cloud Storage, and Dataflow; Google Cloud Platform experience is preferred.
  • Practical experience with large language models, particularly models such as Gemini Flash, and understanding of their deployment and fine-tuning, including prompt engineering, agent orchestration, context-window management, and output validation.
  • Strong background working with large datasets, data warehousing such as Snowflake and BigQuery, and analytics platforms.
  • Solid understanding of software development best practices, scalable system design, and microservices architectures.
  • Analytical skills and a track record of solving complex, ambiguous problems using AI and machine learning techniques.
  • Communication and presentation skills to articulate complex technical concepts to technical and non-technical audiences, including senior leadership.
  • Willingness to be hands-on with prototyping, proof-of-concepts, and guiding implementation.

Responsibilities

  • Define the architecture of AI and machine learning solutions for new product offerings, ensuring scalability, performance, quality, and reliability in a cloud-native environment.
  • Architect AI systems that derive actionable insights from test-run logs and analytics data, including identifying patterns, anomalies, and performance trends.
  • Design AI solutions integrating with the existing error-reporting product to analyze production issues for mobile and web applications and provide deeper understanding and predictive capabilities.
  • Develop architectures that combine insights from test runs and production data to create a holistic view of application quality and user experience.
  • Architect AI models and systems that automatically identify test-run failures, diagnose root causes, and suggest potential fixes or optimizations.
  • Design AI-driven capabilities to assist in generating test cases and improving test coverage and efficiency.
  • Use Google Cloud Platform services and integrate self-hosted Gemini Flash models for text generation and understanding.
  • Collaborate with data engineering teams to define and optimize data pipelines, ensuring efficient data flow from sources such as Snowflake, with an eye toward Google BigQuery, to AI models.
  • Identify opportunities to improve the delivery process with AI tools and validate feasibility.
  • Provide technical leadership and mentorship to engineering teams implementing and deploying AI and machine learning solutions, and participate in AI governance projects.
  • Evaluate advancements in AI and machine learning, technologies, and methodologies to enhance product offerings.
  • Work with product management, engineering teams, and senior leadership to translate business requirements into technical AI solutions and roadmaps.

Desired Qualifications

  • Familiarity with software testing, quality assurance, DevOps, or application performance monitoring.
  • Experience with MLOps practices and tools for managing the machine learning lifecycle.
  • Contributions to open-source AI and machine learning projects or relevant publications.
  • An advanced degree in Computer Science, AI, Machine Learning, or a related quantitative field.

About the Company

Sauce Labs

Automated cross-browser web and mobile testing

Sauce Labs provides a continuous testing and error reporting platform that helps teams develop, deliver, and update high-quality code quickly. It runs tests on real devices and emulators in the cloud, collecting results to give a 360-degree view of user experience across browsers, OSes, and devices. The platform surfaces failures and performance issues to ensure apps look and behave correctly in all environments. Its goal is to help teams ship reliable software faster by catching issues early and delivering consistent user experiences.

Company size
201-500
Company stage
Early VC
Total funding
$151M
Headquarters
San Francisco, CA
Founded
2008

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