Software Engineer II

Microsoft•Redmond, WA

3d•$102,100 - $219,200

About The Position

As a Software Engineer II in Agentic Engineering Productivity, you will build LLM-powered agents that turn intent into tested, reviewable changes, maintain build pipelines and internal tools, and drive cross-team initiatives from planning through delivery. You will work with infrastructure, security, and product services teams, owning your area end to end. This individual-contributor role combines hands-on development with practical judgment about what to automate and where human control is needed. Success is measured by verified engineering outcomes rather than code generation volume. You will use measures such as validated task completion, review usefulness, human intervention and rework, cycle time, defects, and build-pipeline health to guide decisions and keep stakeholders informed of status and risks. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. Employees bring a growth mindset, innovate to empower others, and collaborate toward shared goals, guided by respect, integrity, accountability, and inclusion.

Requirements

Bachelor's degree in Computer Science or a related technical field and 2+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Proficient coding, debugging, and automated testing skills in C# or C++, with working knowledge of big data, ML, NLP, or search technologies.
Hands-on experience building LLM-powered features, applications, or agents that use tools or execute multi-step workflows, beyond personal use of AI coding assistants.
Ability to debug and improve LLM or agent behavior using task-level tests, traces, and failure analysis, and distinguish plausible model output from correct, reproducible engineering results.
Background in cloud services or DevOps, including building and supporting distributed-system features and working knowledge of state management, observability, security, and reliability.
Experience using Azure DevOps and GitHub for project tracking, or technical ability to learn new technologies quickly.
Record of independently delivering features from design to production, with analytical skills and experience in customer engagement and cross-functional collaboration.
Understanding of cloud, AI, and other computing technologies, their business drivers, and emerging trends inside and outside Microsoft.
Prior software development experience and interest in cloud technologies and AI.
Experience working with agile, diverse, geographically dispersed engineering teams and building relationships with senior technical and business leaders.
Self-starter comfortable tackling new challenges and working independently, with strong verbal and written communication skills, including fluency in English.

Nice To Haves

Master's degree in Computer Science or a related technical field and 3+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python; or bachelor's degree in a related field and 5+ years of such experience; or equivalent experience.
Exposure to multi-agent coordination, durable workflow execution, or recovery from interrupted and partially completed agent tasks.
Familiarity with repository-aware context retrieval, code understanding, or model routing and fallback, including trade-offs among quality, latency, and cost.
Experience contributing to developer tools, build and test infrastructure, CI integrations, automated code review, or repair workflows; comfort with command-line tools, PowerShell, and open-source software.
Experience supporting adoption of AI-powered engineering workflows or running evaluations and experiments that connect agent use to measured engineering outcomes.

Responsibilities

Build and maintain agent capabilities that carry authorized work through implementation, test execution, code review, and remediation, producing pull requests with attributable changes and evidence of checks and results.
Design orchestration steps, tool integrations, and context retrieval for repositories, build and test systems, and CI pipelines; evaluate trade-offs and create well-defined interfaces, durable state, and monitoring.
Write LLM and agent evaluations and regression tests based on engineering tasks; debug failures across models, prompts, context, and tools, and qualify changes before release.
Implement secure, bounded execution with scoped permissions, explicit approval for privileged actions, human review before acceptance, observable and attributable actions, and stop conditions when authorization or evidence is insufficient.
Monitor and maintain engineering build pipelines, investigate infrastructure-related failures, engage partner teams on other failures, and help internal teams integrate pipeline components.
Provide IcM support for team-owned services and serve as an escalation point during outages and investigations.
Collaborate with teams on monthly service reviews to surface engineering-system health and hygiene, and participate in security and services infrastructure initiatives, including geo expansion of team-owned services.
Administer internal tools by managing permissions, deploying technology upgrades, implementing new technology, and improving tool administration, documentation, and processes.
Define requirements and acceptance criteria with stakeholders, help inform feature priorities, and partner with solution engineers to validate designs against business needs.
Drive cross-team engineering initiatives by scoping tasks, estimating timelines and effort, managing milestones, identifying and mitigating risks, and course-correcting to maintain schedules.
Report roadmaps, status, and risks through regular updates, engineering newsletters, and other forums; automate program management using Azure DevOps, GitHub, and Power BI.
Coordinate release plans, communications, testing, and change management with business and engineering teams; compare post-release results with baselines to verify planned benefits.