A

Amazon

Sells products online and rents cloud computing

Principal Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Deep expertise in distributed systems, machine learning inference infrastructure, or large-scale artificial intelligence platform engineering.
  • Demonstrated ability to define technical direction in ambiguous, high-stakes problem spaces with significant customer and business impact.
  • Experience driving cross-functional alignment across science, engineering, and product organizations, particularly where unified ownership across research, runtime, and evaluation accelerates delivery.
  • A track record of delivering production artificial intelligence systems that serve diverse, global customer populations.
  • 12 or more years of non-internship professional software development experience.
  • 8 or more years of experience leading the design or architecture of new and existing systems, including design patterns, reliability, and scaling.
  • Experience as a mentor, technical lead, or engineering team leader.
  • Experience collaborating across multiple organizations and influencing key outcomes.
  • Experience as a technical leader of multiple concurrent projects, driving strategic technical decisions.

Responsibilities

  • Design and own the architecture for artificial intelligence capability routing and orchestration at massive scale, including intelligent query classification, model selection, and fallback strategies across heterogeneous artificial intelligence back ends.
  • Drive latency optimization across globally distributed inference pipelines, including model-serving infrastructure, caching strategies, and real-time performance monitoring to meet customer-facing service-level agreements.
  • Build evaluation and quality-assurance infrastructure, including offline test sets, live-traffic sampling, model and prompt release gating, and automated regression frameworks, to maintain accuracy and reliability as models and locales evolve.
  • Architect systems that support rapid iteration and safe deployment of new artificial intelligence capabilities across global regions, with rollback, experimentation, and observability tooling.
  • Lead the design of core artificial intelligence runtime platforms for end-to-end conversational experiences, including speech processing, intent orchestration, and interaction models beyond rigid turn-taking.
  • Define long-term technical strategy for delivering high-quality, low-latency artificial intelligence experiences to global customers, including evolving model integration patterns.
  • Shape the platform vision to empower internal and external engineers and scientists with modular, reusable platforms that accelerate innovation and support accurate, responsive, reliable conversational experiences at scale.
  • Establish engineering standards and best practices for responsible artificial intelligence deployment, ensuring accuracy, safety, and fairness in shipped capabilities.
  • Influence the artificial intelligence platform roadmap by identifying capability gaps, proposing architectural investments, and partnering with applied science, product, and platform teams.
  • Drive integration of specialized conversational artificial intelligence capabilities from science to production, including reasoning, classification, and language-understanding models.
  • Lead the organization's technical direction and make critical architecture, infrastructure, and systems-design decisions for performance, scalability, resilience, and access patterns.
  • Drive innovation in architectures using generative artificial intelligence models.
  • Design and implement scalable solutions for the organization's technical initiatives.
  • Architect and build large-scale distributed systems that integrate complex datasets and support different access patterns.
  • Mentor and inspire engineers and scientists, fostering technical and professional growth.
  • Collaborate across Amazon to align technical vision and priorities and influence decisions at senior levels.
  • Define best practices for system architecture and engineering processes, maintaining software quality and operational excellence.
  • Lead engineering efforts that enhance customer experiences and business outcomes through Alexa+ and generative artificial intelligence-powered services.

Desired Qualifications

  • Experience designing, building, and operating large-scale, highly available, secure cloud infrastructure.
  • Experience with artificial intelligence software systems, including agents.
  • 15 or more years of full software development life-cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • 10 or more years of highly scalable systems experience.

About the Company

Amazon

Sells products online and rents cloud computing

Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Seattle, WA
Founded
1994

Recently Posted Jobs

Explore more opportunities at Amazon

See more jobs