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As a Principal AI Architect, you will define and drive the end-to-end Cloud + AI + Agentic architecture for next-generation WWL skilling experiences and platforms. You will partner with engineering and product leadership to deliver secure, reliable, scalable, cost-effective AI systems and establish a roadmap for Agentic-era learning experiences spanning consumer and commercial scenarios. This is a high-impact architecture leadership role requiring broad technical depth, cross-team influence, and solid collaboration across engineering, product, data, security/compliance, and partner ecosystems—enabling others to execute at scale through shared standards, reusable patterns, and reference implementations.
Job Responsibility:
Own the reference architecture and technical roadmap for WWL’s AI/Agentic platform capabilities (e.g., orchestration, tools/plugins, memory, retrieval, evaluation, observability, governance).
Translate skilling business objectives into platform investments and architectural decisions, balancing speed-to-value with security, compliance, cost, and long-term maintainability.
Establish clear architectural guardrails and decision frameworks (e.g., “build vs. buy,” “Copilot Studio vs. Foundry,” “RAG vs. fine-tune,” “central vs. federated patterns”).
Lead architecture/design reviews for major initiatives
drive alignment on system boundaries, contracts, dependency management, and resiliency.
Define and standardize architecture patterns (multi-tenant SaaS, event-driven architectures, secure data access, model routing, agent safety controls).
Create reusable templates, “golden paths,” and reference implementations to accelerate engineering delivery across teams and reduce fragmentation.
Embed Responsible AI principles into agentic solution design (human-in-the-loop, safety mitigations, evaluation, transparency, and auditability).
Partner with security and compliance stakeholders to ensure services meet required controls and operational standards, and to drive alignment between policy intent and implementation.
Define secure patterns for prompt/data handling, secrets management, identity, and access governance for AI systems.
Drive architecture that improves reliability, observability, incident response readiness, and cost efficiency across AI-enabled services.
Establish telemetry standards (quality, safety, latency, cost, success metrics) and ensure teams instrument consistently to enable operational excellence at scale.
Design for production: rollout/rollback strategies, evaluation gates, and operational playbooks for AI/agent releases.
Build coalitions across WWL and broader Microsoft engineering/product groups to deliver complex, large-scale initiatives
resolve long-standing misalignments
and hold stakeholders accountable for commitments.
Act as a trusted technical advisor to senior stakeholders, creating clarity, driving alignment, and enabling execution across multiple teams and disciplines.
Mentor engineers
enhance architecture quality, engineering discipline, and Responsible AI rigor.
Contribute to internal technical communities through documentation, brown bags, and reusable engineering guidance—amplifying impact through others.
Embody our culture and values
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience.
Master's Degree in Computer Science, Engineering or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR 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.
10+ experience in software engineering or solution architecture, with demonstrable success building and operating complex systems.
10+ experience designing, implementing, and optimizing AI solutions encompassing data pipelines, model training and serving, and production MLOps.
10 + years of full-stack development across frontend, backend, and cloud infrastructure, with a proficient command of data engineering, AI/ML systems, and deployment architectures.
2+ project experience with NLP and LLM-based systems.
Proficient coding skills in C#, Python, JavaScript, and React.
Proven experience designing and shipping AI/ML GenAI solutions, including one or more of: Retrieval-Augmented Generation (RAG), enterprise search, vector retrieval
LLM orchestration and agentic workflows
AI evaluation/monitoring, safety and quality measurement
Demonstrated experience architecting and delivering cloud-native, distributed systems at scale (multi-service systems, reliability, performance, and operability).
Proficient engineering fundamentals and ability to work “hands-on when needed” (prototyping/reference implementations, architectural spike investigations, debugging complex issues).
Track record of cross-team influence—driving alignment and execution across multiple disciplines and stakeholders.
Ability to communicate clearly with technical and non-technical audiences