Senior Enterprise Architect Consultant (AI) (Indianapolis)
IWU is seeking a Senior Enterprise Architect Consultant for AI and Software (Independent Contractor - 1099 / Contract-to-Hire) to add their expertise to major university wide application refactoring and software development efforts to Sovereign AI-First platforms and to advance large-scale technology reorganization projects. Learn more about IWU ABOUT IWU TECHNOLOGY IWU has been a pioneer and industry leader in technology ‑ enabled education , being one of the first universities to establish distance learning in the early 1990s. University leadership is rekindling our entrepreneurial spirit and has mandated and funded an organization-wide initiative to re-platform major existing systems to AI-FIRST/AI-NATIVE driven technology platforms . We are standing up two additional data centers in an active/active configuration at premium commercial colocation facilities for on-premises sovereign AI platforms and application solutions that will become the foundation for how we deliver intelligent internal and commercially offered products. IWU’s technology teams currently comprise about 90 people delivering infrastructure, application, and integration services across the university . IWU’s technology teams are growing and looking for the best and brightest Christ-followers to help us fully embrace the AI revolution . ABOUT THE ROLE: Architecture and Standards We are seeking expertise to help define excellent, end-to-end, enterprise-class best practices by defining architecture, first principles, standards, and governance for all traditional software platforms, AI platforms, tools, third-party applications, and integrations and helping with vendor evaluations and tool selection. Additionally, we have large scale requirements and significant funding to design and build new advanced AI infrastructure and application . AI Platform Design Design the GPU/NPU and accelerator fabric in partnership with infrastructure engineering – node profiles, interconnect topology (NVLink / RoCE / InfiniBand). Design the model serving and inference platform – including runtime selection, multi-tenant scheduling, quantization strategy, KV-cache management, autoscaling, and SLO enforcement. Design the AI data plane – vector stores, embedding pipelines, RAG retrieval architecture, feature stores, and the integration patterns that connect AI workloads to enterprise systems of record. Design the agent and orchestration layer – tool-use, function-calling contracts, guardrails, prompt management, and evaluation harnesses. Define MLOps and LLMOps patterns – model registry, fine-tuning pipelines, evaluation, canary and shadow deployment, drift detection, and rollback. Solution Design and Delivery We also have AI-based solutions to design and implement for the administration and delivery of practical, operational educational experience for IWU students and staff, and for other universities as a SaaS offering. Governance and Multi-Tenancy Establish AI governance in partnership with Risk, Legal, and Compliance – model inventory, data classification controls, prompt and output logging, content filtering, red-teaming cadence, and responsible AI policy enforcement. Design tenant isolation, data segregation, and zero-trust patterns suitable for a commercial SaaS platform serving multiple businesses, business units, and sensitivity classes. Practitioner Influence You will be partnering with Infrastructure, Network, Security, Data, and Application Solution Designers to ensure AI requirements are reflected in their respective domains. You will be expected to maintain awareness of the rapidly evolving AI landscape and translate research and vendor advances into pragmatic, enterprise-ready guidance. You will be a senior individual contributor with significant influence : you will set technical direction, establish AI reference architecture, define the standards every solution must meet, and partner with solution designers, infrastructure, security, data, and development teams to deliver and advance that architecture in production. Champion AI implementations with faculty, business, and technology staff. WHAT WE ARE LOOKING FOR: Required According to Indiana Wesleyan University policy, all employees and contract-to-hire contractors must possess a strong Christian commitment and adhere to the standards outlined in the IWU Community Lifestyle Statement . 10 years of progressive experience in enterprise software , infrastructure, or platform architecture, with 5 years focused on machine learning, AI platforms, and adjacent disciplines . Demonstrated experience architecting production AI systems at enterprise scale – not just prototypes or proofs of concept. Familiarity with agent frameworks and orchestration (and custom orchestrators) and the operational realities of running them in production. Experience with fine-tuning and post-training workflows including data curation, evaluation, and lineage. Experience with MLOps platforms and model registries in regulated environments. Deep, firsthand knowledge of modern LLM serving and inference – quantization, batching, KV-cache, tensor and pipeline parallelism, throughput vs. latency trade-offs. Strong working knowledge of GPU and accelerator infrastructure – NVIDIA data-center GPUs, drivers, CUDA, MIG partitioning, GPU operators, and emerging NPU accelerator alternatives . Experience designing for on-premises and colocation environments – VMware, Kubernetes, bare-metal provisioning, software-defined storage, and high-performance networking (RoCE / InfiniBand / 100G Ethernet). Experience with vector databases and retrieval architectures and the embedding pipelines that feed them. Experience integrating enterprise systems with Microsoft Entra ID and Okta (OIDC, SAML, conditional access, app registrations, managed identities). Experience operating across multi-site active/active topologies , including data replication, traffic management, and DR design at the application and platform layers. Ability to write clear, decision-quality architecture documents and to present complex trade-offs to both technical and non-technical executive audiences . Previous experience as an analyst, application developer, and architect . Bachelor’s degree in Computer Science, Engineering, or a related technical field – or equivalent demonstrated experience . Strongly Preferred Background in a regulated or compliance-sensitive industry (education/FERPA-Title-IV, financial services/GLBA, healthcare/HIPAA, insurance, public sector, defense). Familiarity with data center standards (TIA-942, BICSI) and ITIL service management. Experience with Infrastructure as Code (IaC) and GitOps patterns at scale. Contributions to open-source AI or infrastructure projects , conference talks, or published technical writing. Relevant certifications (NVIDIA-certified architect, CKA / CKAD, TOGAF, CISSP). How You Work You make decisions with incomplete information , document the reasoning, and revise them as new evidence arrives. You optimize for outcomes and operability, not novelty – you choose boring technology when boring is right, and bleeding-edge when the business case justifies it. You write things down. Architecture without a written artifact does not exist . You collaborate generously across teams and treat every conversation as an opportunity to raise the bar around you. You stay curious . The AI field moves quickly, and you have a system for keeping up. WHY THIS ROLE? Greenfield platform . You are not inheriting a sprawling cloud estate – you are designing the AI foundation for the enterprise from a clean architectural slate. Real budget, real hardware . There has been a serious investment and commitment to enterprise-class AI and infrastructure capacity, multi-site colocation, and dedicated platform engineering. Strategic visibility . The AI platform is a board-level priority. Your work will be visible to the executive team and critically material to the business. Technical depth . This is not a cloud architect role. We have made a deliberate, strategic decision to run sovereign AI workloads on infrastructure we own and operate. Because we operate on our own infrastructure, you will work end-to-e
