Software Engineer 2

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Software Engineering

Software Engineer 2 at Microsoft's CoreAI organization, specifically within the Responsible AI group. The role focuses on building customer-facing AI services with a scalable, sustainable, high-performance architecture, emphasizing high availability, low latency, and robustness. Responsibilities include designing and developing large-scale distributed cloud services, leading project development, taking end-to-end ownership of the development lifecycle, and upholding software engineering best practices. Experience with ML model development, release, and operations, as well as AI tools across the SDLC, is preferred.

What you'd actually do

  1. Design and develop large-scale distributed cloud services and solutions with a focus on high availability, scalability, robustness, and observability.
  2. Lead project development across the organization and work with subject matter experts and stakeholders to drive development and release plans.
  3. Take end-to-end responsibility for the development lifecycle and production readiness of the services you build and drive the team’s DevOps culture.
  4. Drive and uphold the best practices of modern software engineering through code and design reviews and take effective service decisions based on data and telemetry.
  5. Understand Microsoft businesses and collaborate with stakeholders towards cohesive, end-to-end experiences for Microsoft customers.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field
  • 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • Ability to meet Microsoft, customer and/or government security screening requirements

Nice to have

  • 2+ years of technical engineering experience designing and delivering highly available, large-scale cloud services and distributed systems.
  • Experience with machine learning model development, release, and operations.
  • Demonstrate depth of knowledge and understanding of software architecture, design tradeoffs, and practices of mature DevOps culture.
  • Experience using appropriate artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC) in a disciplined manner.
  • Experience in any one or more of the following areas: Software Engineering IC3

What the JD emphasized

  • Responsible AI
  • high availability
  • scalability
  • robustness
  • observability
  • high performance
  • low latency

Other signals

  • Responsible AI services
  • customer-facing AI services
  • scalable and sustainable architecture
  • high performance, low latency, and high availability
  • design of new AI services and integration with existing services