Significant experience in enterprise architecture, cloud architecture, software engineering, or platform engineering.
Recent experience designing and deploying production generative AI solutions.
Strong working knowledge of the Microsoft cloud and AI ecosystem, including Microsoft 365 Copilot and Azure AI.
Hands-on experience integrating commercial AI models through APIs.
Strong understanding of RAG architectures and enterprise data integration.
Familiarity with standards like Model Context Protocol (MCP) and OpenTelemetry.
Experience designing secure systems in regulated environments.
Responsibilities
Define and evolve Karman's enterprise AI reference architecture.
Establish architectural patterns for model access and orchestration.
Develop technical standards for Microsoft AI capabilities.
Evaluate external platforms based on security and business needs.
Design architectures that support portability using APIs and open protocols.
Build proofs of concept and reusable components.
Provide hands-on support for complex AI use cases.
Benefits
Medical, dental, and vision insurance
401(k) with company match
Paid time off
Health Savings Account (HSA) with company contribution
Flexible Spending Accounts (FSA)
Company-paid life and AD&D insurance
Short- and long-term disability coverage
Tuition reimbursement
Full Job Description
In this senior individual-contributor role, you will translate Karman's enterprise artificial intelligence (AI) strategy into secure, scalable, and reusable architectures that accelerate responsible adoption across the organization. You will shape technical patterns, build reference implementations, evaluate emerging technologies, and establish guardrails that enable governed self-service. Partnering closely with AI/Data & Automation, Business Systems, Cybersecurity, Infrastructure, and functional teams, you will provide hands-on technical leadership that strengthens solution quality, operational consistency, and enterprise readiness.
Responsibilities
Defines and evolves Karman's enterprise AI reference architecture.
Establishes architectural patterns for model access, retrieval-augmented generation (RAG), orchestration, agents, application programming interfaces (APIs), evaluation, observability, and cost management.
Develops technical standards for Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and other approved enterprise AI capabilities.
Evaluates external platforms and models based on security, performance, cost, and business needs.
Designs architectures that support portability using APIs, abstraction layers, open protocols, and exit strategies.
Builds proofs of concept, reference implementations, reusable components, and technical accelerators.
Provides hands-on support for complex AI use cases, including RAG solutions, agentic workflows, model-integrated applications, and automation.
Establishes reusable templates, patterns, guardrails, and documentation to enable governed self-service.
Translates enterprise AI governance requirements into technical controls for identity, access, logging, monitoring, classification, retention, and human oversight.
Defines evaluation, observability, quality, operational readiness, incident response, and lifecycle management standards for AI solutions.
Required Qualifications
Significant experience in enterprise architecture, cloud architecture, software engineering, or platform engineering.
Recent experience designing and deploying production generative artificial intelligence (AI) solutions.
Strong working knowledge of the Microsoft cloud and AI ecosystem, including Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Entra ID, Purview, and Microsoft security technologies.
Hands-on experience integrating commercial AI models through APIs and building model-enabled applications.
Strong understanding of RAG architectures, agent patterns, tool use, model orchestration, vector search, and enterprise data integration.
Familiarity with standards and technologies such as Model Context Protocol (MCP), OpenTelemetry, open-weight models, and modern inference platforms.
Experience designing secure systems in regulated or high-assurance environments.
Ability and willingness to write code, build prototypes, review designs, and troubleshoot technical issues.
Strong written and verbal communication skills with the ability to explain complex technical tradeoffs to technical and executive audiences.
Preferred Qualifications
Experience in aerospace, defense, government, manufacturing, financial services, or other regulated industries.
Experience with GCC High, sovereign cloud, restricted environments, or controlled-data architectures.
Familiarity with frameworks such as Cybersecurity Maturity Model Certification (CMMC), National Institute of Standards and Technology (NIST) Special Publication 800-171, Controlled Unclassified Information (CUI), International Traffic in Arms Regulations (ITAR), NIST AI Risk Management Framework (RMF), and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 42001.
Experience integrating AI with enterprise platforms such as enterprise resource planning (ERP), product lifecycle management (PLM), manufacturing execution systems (MES), customer relationship management (CRM), productivity, analytics, and workflow systems.
Familiarity with graphics processing unit (GPU) infrastructure, self-hosted models, fine-tuning, and private inference environments.
Relevant Microsoft, cloud, architecture, or security certifications.
This position requires U.S. person status under U.S. export control laws, including U.S. citizens and nationals, lawful permanent residents, refugees, and asylees.
Benefits
Medical, dental, and vision insurance
401(k) with company match
Paid time off
Health Savings Account (HSA) with company contribution
