Architect Jobs

About The Position

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field and at least 6 years of technical engineering experience designing and building complex software systems, distributed systems, or cloud platforms, or equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

• Master's degree in Computer Science, Engineering, or a related technical field and at least 8 years of relevant technical engineering experience; or a bachelor's degree in a related field and at least 12 years of relevant experience; or equivalent experience.
• Significant experience architecting production-scale distributed systems, multi-tenant services, enterprise platforms, cloud infrastructure, or AI-powered systems.
• Experience establishing reference architectures, architectural principles, platform standards, system boundaries, and reusable patterns across multiple teams or organizations.
• Experience designing strong tenant isolation across identity, authorization, data, compute, configuration, networking, and operations.
• Experience defining production architecture for generative AI, including model orchestration, RAG, retrieval, memory, context management, reasoning, tool use, evaluation, grounding, and safety.
• Experience architecting agentic or multi-agent systems, including planning, tool invocation, orchestration, memory, state, delegation, communication, policy enforcement, and bounded execution.
• Deep understanding of identity, authentication, authorization, RBAC, least privilege, delegated authorization, workload and service identities, agent identities, and multi-tenant security boundaries.
• Experience defining secure patterns for integrating AI systems with enterprise data, services, APIs, plugins, tools, and distributed execution environments.
• Experience designing RAG architectures, including ingestion, indexing, embeddings, retrieval, re-ranking, provenance, grounding, authorization-aware retrieval, and evaluation.
• Experience with cloud architecture, Kubernetes, containerized services, compute, storage, networking, service-to-service communication, configuration management, Infrastructure as Code, automated deployment, and CI/CD.
• Experience architecting highly available and resilient services, including dependency failure, capacity constraints, throttling, graceful degradation, fault isolation, recovery, and disaster scenarios.
• Experience defining observability, diagnostics, health monitoring, deployment validation, and operational architecture for large-scale distributed systems.
• Experience identifying architectural coupling and evolving production systems toward modular, reusable, configurable, extensible, and scalable platform architectures.
• Experience evaluating tradeoffs involving security, reliability, scalability, performance, cost, operational complexity, developer productivity, and time-to-market.
• Ability to influence technical strategy and align engineering organizations around shared architectural direction without direct organizational authority.
• Strong technical communication skills, including explaining complex architectures and tradeoffs to engineers, architects, product leaders, security experts, and senior leadership.
• Ability to mentor senior technical leaders and raise architectural and engineering capabilities across an organization.

Responsibilities

• Define the architectural vision and long-term technical strategy for the Perception Platform and establish reference architectures for production-grade AI capabilities.
• Define scalable multi-tenant architectures and patterns for tenant isolation, identity, authorization, configuration, data protection, deployment, sovereignty, compliance, and operations.
• Establish architectural principles, system boundaries, and reusable abstractions across platform infrastructure and AI capabilities to reduce fragmentation and tenant-specific coupling.
• Drive architectural convergence across distributed systems and engineering teams through shared patterns, interfaces, contracts, and platform capabilities.
• Define automation-first architecture for tenant provisioning, configuration, deployment, validation, upgrades, migrations, lifecycle management, and operational readiness.
• Design architectures that accommodate variation in tenant configuration, service availability, infrastructure, networking, identity, security, data residency, sovereignty, and compliance.
• Establish architecture for scalable RAG systems, including ingestion, indexing, retrieval, context construction, grounding, provenance, evaluation, governance, and authorization boundaries.
• Define architectures and principles for agentic and multi-agent systems, including planning, reasoning, tool use, delegation, collaboration, memory, human oversight, failure recovery, and bounded execution.
• Define identity, authentication, and authorization architecture for AI systems, including user, workload, service, and agent identities, RBAC, delegated authorization, least privilege, and secure context propagation.
• Establish guardrails to preserve tenant isolation and authorization across retrieval, reasoning, planning, memory, and execution, and validate agent plans and tool interactions against applicable policies.
• Define AI safety, security, and trust-boundary architecture, including defenses against prompt injection, unsafe tool invocation, cross-tenant exposure, untrusted content, and privacy or compliance violations.
• Establish architecture for AI memory and state management, including isolation, authorization-aware retrieval, lifecycle, retention, deletion, provenance, privacy, and compliance.
• Define architectural expectations for automated validation, testing, and conformance across correctness, isolation, authorization, security, reliability, deployment readiness, and compatibility.
• Establish observability, monitoring, diagnostics, and operational architecture for platform health and troubleshooting distributed services and AI workflows.
• Define strategies for resilience, scale, capacity, dependency management, graceful degradation, disaster recovery, and failure isolation across globally distributed services.
• Identify systemic architectural dependencies and guide production systems toward modular, configurable, reusable, secure, and scalable architectures with practical migration strategies.
• Lead architecture reviews and advise on build-versus-reuse decisions, service boundaries, data and API contracts, technology choices, dependencies, and tradeoffs.
• Partner with engineering and product leadership to translate customer and business needs into architectural roadmaps and strategic technology investments.
• Influence architecture across Microsoft Security and related platform organizations, aligning direction and encouraging reusable patterns while preventing duplication and fragmentation.
• Mentor senior engineers and architects and promote rigorous design, technical depth, engineering excellence, and long-term systems thinking.