Principal Software Engineering Manager
Microsoft
As a Principal Software Engineering Manager drive a talented team of engineers on a mission to create & operate a trusted decision-intelligence system that delivers actionable insights and enables rapid action. Enable high-quality predictive insights that protect and grow Windows. In this role, you will build a new engineering team delivering the intelligence fabric that influences Windows strategy and commercial outcomes. You will lead a cross-functional team spanning software engineering, data engineering, and applied ML/LLM integration. You will be expected to have strong technical depth and comfort presenting to VP/CVP audiences.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Build and lead a high-impact engineering organization
- Recruit, develop, and lead an organization of software and data engineers (hiring plan, team topology, career growth, performance management), and create an inclusive, high-accountability culture.
- Translate strategy into executable roadmaps and deliver predictable outcomes through clear prioritization, ownership, and operating mechanisms.
- Raise the engineering bar through strong craftsmanship: design reviews, code reviews, test strategy, CI/CD quality gates, and pragmatic documentation.
Own delivery of complex full-stack services
- Own delivery of full-stack services that combine product engineering with data/ML capabilities (data ingestion, feature engineering, model integration, evaluation, and production operations).
- Deliver services and data workflows that synthesize multi-source signals into high-quality, timely insights for engineering and business stakeholders.
- Apply human-in-the-loop & evaluation approaches to validate the quality, clarity, and reliability of insight-producing systems.
Architect secure, scalable, efficient, high-reliability services
- Drive architecture for reliable, secure, and scalable services (distributed systems, APIs, event-driven architecture), with strong operational excellence (on-call, SLOs, incident response).
- Set technical direction and guardrails for LLMs/agents in development and production, including secure-by-design patterns for data handling, access control, and tool authorization.
Advance AI-forward engineering practices
Establish and scale AI-forward engineering practices through disciplined, repeatable systems:
- Agentic workflows: Use multi-agent patterns (e.g. generate-review-refine, generator-validator, specialization) to accelerate delivery while maintaining high engineering standards.
- Evaluation & quality gates: Define test-first workflows, automated checks, and structured review to validate correctness, maintainability, and regressions, including for AI-generated code.
- Safety & responsible use: Apply security and privacy guardrails for LLM/agent use (least privilege, data handling, tool authorization, and mitigations for prompt injection and sensitive-data leakage).
- Tooling & enablement: Curate approved tooling and team conventions (prompts/instructions, reusable patterns, documentation) and instrument developer productivity and quality outcomes.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Experience as an engineering manager leading managers and/or senior ICs, including hiring and building teams from scratch (or significant expansion) and operating in an ambiguous, fast-moving environment.
- Executive presence and stakeholder leadership: ability to engage, influence, and align across organizations/divisions; communicate clearly with senior leaders including VP/CVP audiences.
- Strong software engineering foundation with experience building and operating production services (design, coding, testing, deployment, and on-call operations).
- Demonstrated ability to drive engineering excellence: CI/CD, automated testing, observability, incident management, and measurable reliability outcomes (SLOs/SLIs).
- Experience collaborating closely with data engineering: batch/stream processing, data modeling, orchestration, and reliability of data pipelines.
- Hands-on experience using AI-assisted development tools in production engineering environments (e.g., LLM-powered IDE workflows, code generation, automated refactoring/testing) and the ability to operationalize them into consistent team practices.
Preferred Qualifications:
Developer productivity and platform thinking
- Experience building platforms for developer productivity (internal developer platforms, golden paths, templates, service scaffolding, or policy-as-code).
LLM / agent system design
- Experience with LLM system design: retrieval-augmented generation (RAG), tool/function calling, agent orchestration, evaluation harnesses, prompt/version management, model selection/routing, and monitoring for quality and safety.
- Preferred: experience designing multi-agent architectures and evaluation-driven development workflows (automated evaluation harnesses, quality gates, and monitoring to improve agent outputs over time).
- Implementation experience with MCP and A2A-style agent-to-agent patterns: defining tool contracts, hardening connectors, integrating auth/permissions, and operating these systems reliably in production at scale.
- Preferred: depth securing LLM-enabled applications and agents (threat modeling, red teaming, and practical mitigations).
Data-to-insight systems and semantic modeling
- Experience designing systems that transform complex data into actionable guidance, dashboards, or programmatic outputs.
- Experience working with contextual or semantic representations of complex systems (e.g., entity models, organizational or device context, or knowledge-graph-like structures).
- Experience building low-latency or event-driven systems that support timely insight generation or operational decision support.
Cloud and multidisciplinary leadership
- Experience building on Azure’s data + AI stack to deliver production-grade systems (data engineering, model integration, evaluation, and operations).
- Experience leading teams across software + data/analytics/ML boundaries, including shared ownership models and clear data contracts.
- Background in security/privacy for AI systems (data governance, red teaming, secrets management, least privilege, and supply-chain security).
What Success Looks Like
- You have hired and onboarded a high-performing team with the right mix of software and data engineering skills, with clear roles, expectations, and growth plans.
- Your team ships reliably: shorter lead times, high-quality releases, and strong operational metrics (availability, latency, defect escape rate).
- AI-assisted development is implemented as a disciplined system: repeatable workflows, quality gates, measurable productivity gains, and safe data handling.
- Core data pipelines and ML/LLM integrations are robust, observable, and cost-efficient, with clear data contracts, evaluation-driven model iteration (including choosing the right model for the task), and disciplined context engineering loops (summarize, validate, refresh context) to keep agent behavior stable over time.
- Stakeholders receive clearer, more consistent insight from unified systems, enabling faster understanding and action within their domains.
#BICJOBS
Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.