Senior/Principal Software Engineer - CoreAI

Within CoreAI, Foundry IQ powers rich knowledge experiences for applications of all kinds, including agentic workloads. We bring together the best of Microsoft AI across content understanding, search relevance, and diverse knowledge sources to help developers build intelligent, enterprise-ready solutions.

As a Principal Software Engineer, you will shape the end-to-end customer and developer experience for FoundryIQ. This organization-level role sets technical direction across product and service boundaries, turns ambiguous opportunities into durable outcomes, and helps customers discover, adopt, and succeed with secure, reliable AI capabilities at global scale.

We are looking for a principled technical leader who thrives in ambiguity, exercises sound judgment with incomplete information, and adapts as customer needs, technology, and business priorities evolve. You will raise the engineering bar by creating clarity, building alignment, and enabling teams to move quickly without compromising security, reliability, or long-term maintainability.

You will be a trusted technical voice for the developers who use and build our platform, connecting customer and internal developer needs with product and engineering strategy. Your influence across organizational boundaries will improve how developers adopt and operate enterprise-ready AI workloads.

You will advance engineering excellence across the full product lifecycle, helping the organization deliver high-quality developer experiences with speed and confidence. Your impact will span UX flows, Agentic harnesses, samples, SDKs, and web services, with an emphasis on scalable practices and continuous learning.

Success in this role will be measured by durable organization-level outcomes: faster developer onboarding and delivery, increased adoption of platform capabilities, improved engineering health, reduced operational risk, and stronger technical practices that enable teams to move quickly and safely.

Lead the principled adoption and continuous improvement of AI tools and Responsible AI practices across the software development lifecycle. Establish accountability for AI-generated assets, define scalable processes and tools, use engineering health metrics to measure progress, and share learnings across the organization.

Set technical direction for production services and improve engineering quality through automation, analysis, debugging, telemetry, and retrospectives. Strengthen diagnosability, incident prevention, secure and privacy-preserving operations, least-privilege practices, and code quality.

Raise the technical and engineering bar across the organization by defining and modeling principled practices, mentoring technical leaders, and creating reusable mechanisms that help teams improve quality, velocity, and operational discipline at scale.

Build an inclusive and safe engineering culture where people have the clarity, autonomy, and accountability to do their best work. Model constructive technical debate, encourage learning from outcomes, and create space for others to lead.

Create clarity as goals, customer needs, technologies, and constraints evolve. Reframe ambiguous problems, communicate changes in direction, and help teams learn, adapt, and maintain momentum through shifting priorities.

Lead cross-group planning and execution by translating long-term vision and ambiguous problems into clear decisions, milestones, and measurable outcomes. Drive estimation and capacity planning, negotiate scope and technical tradeoffs, resolve blockers, and adjust execution as goals and constraints change.

Balance delivery speed with security, privacy, compliance, reliability, and operational readiness. Establish disciplined practices for validation, flighting, rollback, incident response, and disaster recovery, and use operational evidence to reduce risk.

Partner with internal and external developers, customers, and stakeholders to validate requirements, technical feasibility, and product outcomes. Translate qualitative feedback, usage data, and success metrics into prioritized improvements, including accessibility, globalization, security, and privacy requirements.

Influence technical strategy and product direction across teams without relying on formal authority. Build shared understanding among developers, technical leaders, product partners, and stakeholders, surface disagreements early, and secure commitment to cohesive, enterprise-ready experiences.

Required Qualifications

• Bachelor’s Degree in Computer Science, Engineering, or related field AND 4+ years of technical engineering experience building and operating cloud services OR equivalent experience.

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.  

Preferred Qualifications

• 4+ years of technical leadership and architecture at the product scope. 
• Experience owning end-to-end customer and developer experiences across one or more product surfaces including defining requirements and driving delivery. 
• Experience with distributed systems and engineering systems. 
• Experience designing and delivering secure services, including identity/access patterns and privacy/compliance considerations. 
• Lead AI-assisted engineering tools to improve SDLC quality and velocity, including responsible use of AI-generated assets for a organization. 
• Strong customer empathy with a track record of using qualitative and quantitative feedback to iterate product experiences. 
• Highly effective at creating significant impact within intricate codebases and large organizations. 
•  Experience building AI-powered product capabilities and/or search, retrieval, or data/knowledge services at scale.