Principal Software Engineer, Dynamics Customer Experience Applications

Microsoft

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Redmond, WA
Salary
$142,800–$274,800 / yr
Posted
16 days ago
Freshness
Confirmed live yesterday
Closes
Feb 21, 2027

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $203k
This role $209k
$127k most similar roles pay here $291k

This role pays more than 62% of similar roles. Most pay $174,600–$231,000 — the shaded band above. At the midpoint, this role pays about $209k versus about $203k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 598 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 586 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer, Dynamics Customer Experience Applications

Principal Software Engineer - Dynamics Customer Experience Applications team As a Principal Software Engineer on the Dynamics Customer Experience Applications team, you will provide technical leadership for the architecture, design, and operation of intelligent capabilities within Dynamics 365 Contact Center. You will solve complex engineering problems involving distributed cloud services, applied AI, data, security, and reliability to build scalable, production-ready systems. Your daily work involves defining technical strategies for globally distributed services, managing high-impact projects, and mentoring engineers while ensuring quality and security by design. The role requires proficiency in C, C++, C#, Java, JavaScript, or Python, alongside experience with Azure, WebSockets, gRPC, and GitHub-based CI/CD workflows. You will specifically address the challenge of creating an AI-first solution that integrates Dynamics 365, Office 365, and other cloud services to provide predictive application scenarios across various devices and form factors.

What does a Software Engineer earn in Washington?

Median $202800 from 326 postings across 28 companies.

See salary data

What you'll do

  • Define and evolve end-to-end architecture for complex, AI-enabled customer experience capabilities across distributed cloud services.
  • Lead the technical strategy and implementation of applied AI systems including model selection, evaluation, and lifecycle management.
  • Own the full lifecycle of critical components from initial problem definition through deployment and long-term operational health.
  • Develop high-quality production code to resolve complex design, performance, and debugging challenges in distributed systems.
  • Ensure system quality by designing for security, compliance, observability, and automated incident response.
  • Resolve high-severity live-site issues by conducting root-cause analysis and implementing systemic prevention measures.
  • Mentor engineers and establish reusable patterns to improve the overall engineering standards of the organization.
  • Translate business requirements into multi-release technical investments and clear engineering plans across multiple teams.

What we're looking for

  • Bachelor's Degree in Computer Science or related field and 6+ years of technical engineering experience with coding in languages like C, C++, C#, Java, JavaScript, or Python (or equivalent).
  • Ability to pass the Microsoft Cloud background check.
  • Experience architecting and delivering large-scale, production cloud services across multiple teams or complex dependencies (preferred).
  • Experience designing, building, and troubleshooting scalable, resilient, event-driven systems including asynchronous processing and media-processing workflows (preferred).
  • Proficiency in WebSockets, gRPC, GitHub-based CI/CD workflows, and Azure Service Fabric (preferred).
  • Expertise in diagnosing cross-service failures using logs, telemetry, correlation IDs, and distributed traces (preferred).
  • Experience with tools like GitHub Copilot and Claude for implementation, debugging, and rapid prototyping (preferred).
  • Experience shipping generative AI or large language model capabilities with rigorous evaluation and safety practices (preferred).

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