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Senior and Principal Software Engineers - Azure AI Search

United States, Redmond 119800.00 - 234700.00 USD / Year · Job Posted April 06, 2026
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Job Description

Join Azure AI Search Engineering Foundations as a Senior or Principal Software Engineer and help transform how we build, validate, ship, and operate AI Search at scale—securely and reliably. You’ll improve the end-to-end developer experience across inner-loop productivity and outer-loop CI/CD, validation, release, and operations by turning ambiguous engineering pain points into practical tooling, automation, and standards that teams adopt.

Job Responsibility

  • Own and deliver engineering foundations work end‑to‑end—spanning design, implementation, testing, rollout, and iteration—to improve the inner‑ and outer‑loop developer experience across Azure AI Search.
  • Partner closely with feature, platform, and infrastructure teams to understand developer pain points, translate requirements into pragmatic tooling, automation, and process improvements, and drive adoption through collaboration and iteration.
  • Prototype, evaluate, and integrate AI‑assisted engineering tools and modern workflows that measurably improve developer productivity, quality, reliability, and operational confidence.
  • Design and incrementally deliver scalable, reliable, and efficient solutions across CI/CD pipelines, build and test infrastructure, validation frameworks, automation, and operational tooling—using data and feedback to validate impact.
  • Apply a security‑first mindset in daily engineering work, including secure coding practices, threat modeling, identity and secrets hygiene, and compliance‑aware design.
  • Navigate ambiguity by breaking down complex problems, proposing options and tradeoffs, aligning stakeholders around a clear direction, and communicating progress, risks, and outcomes effectively.
  • Lead by example through strong technical judgment, mentorship, and collaboration, helping raise the bar for engineering practices while fostering an inclusive, high‑trust team culture.
  • Define and influence a high‑quality developer experience for Azure AI Search by setting standards, establishing best practices, and driving improvements that enable engineering teams to thrive.
  • Deliver results with a focus on measurable outcomes, such as reduced build and test times, faster PR validation, improved pipeline reliability, and decreased manual toil.

Requirements

  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
  • Experience building or operating services on Azure (or comparable cloud platform).
  • Experience with secure engineering practices (e.g., threat modeling, secure coding, secrets management, managed identities, authentication/authorization, certificates).
  • Experience building developer platforms or frameworks (e.g., validation frameworks, test infrastructure, internal SDKs, reusable libraries).
  • Experience evaluating or integrating AI-assisted developer workflows in a production engineering environment.
  • Master's Degree in Computer Science or related technical field OR equivalent experience.
  • Successful track record delivering production software end-to-end (design, implementation, testing, rollout) for a service or platform, with clear ownership of at least one meaningful component or capability.
  • Successful track record improving engineering productivity through tooling, automation, build/test infrastructure, CI/CD, or operational tooling—demonstrated by measurable outcomes (e.g., reduced build/test/validation time, improved pipeline reliability, reduced manual steps/toil).
  • Successful track record operating and improving reliability of software systems by diagnosing issues from logs/metrics/traces, driving fixes, and validating improvements (e.g., reduced incident recurrence, improved operational health signals).
  • Successful cross-team collaboration: partnered with stakeholders to clarify ambiguous requirements, evaluate tradeoffs, and deliver agreed outcomes (e.g., shipped incremental milestones, communicated risks and dependencies clearly).
  • Successful track record gathering and confirming requirements by leveraging multiple feedback channels and data (e.g., partner input, developer signals, productivity metrics) to inform designs and iterative improvements.

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