Scope of Job: The Principal AI Platform Engineer is the company’s first dedicated AI role, responsible for the end-to-end design, build, and governance of the enterprise AI platform. The role owns both surfaces of the AI strategy: Microsoft 365 Copilot for business user AI and AWS Bedrock for enterprise application AI, integrating with enterprise data sources across structured platforms, document repositories, and operational systems. Operating as a senior individual contributor without direct reports, this role drives delivery through a matrixed model, directing cloud, M365, security, and application teams to execute platform workstreams. The role is expected to grow in scope as the AI function matures, with the potential to build a dedicated team over time.
Responsibilities
- Hands-On Engineering & Delivery
- Builds and operates AWS Bedrock infrastructure including Agents, Knowledge Bases, Guardrails, and OpenSearch Serverless RAG pipelines in production environments.
- Configures and governs Microsoft 365 Copilot including sensitivity label policy, Graph connector setup, DLP policy integration, and licensing scope management.
- Develops and maintains AI infrastructure as code (Terraform or AWS CDK) for repeatable, governed deployments across environments.
- Integrates enterprise data sources — including structured data platforms, document repositories, and APIs — into Bedrock-powered workloads, applying appropriate grounding, retrieval, and data access patterns for each source type.
- Builds and maintains platform monitoring, logging, and audit tooling to support governance, compliance, and continuous improvement.
- Platform Architecture & Standards
- Owns and maintains the enterprise AI reference architecture across Microsoft 365 Copilot and AWS Bedrock, ensuring alignment with security, data governance, and compliance requirements.
- Defines and enforces platform standards covering model selection, prompt design, RAG pipeline patterns, retrieval evaluation, and data grounding.
- Leads Architecture Review Board (ARB) submissions for all AI workloads entering production, producing architecture decision records and supporting documentation.
- Evaluates emerging AI capabilities and tooling, provides structured adoption recommendations with business value and risk framing.
- Ensures AI platform controls align with applicable regulatory and enterprise security frameworks.
- Governance & Risk Management
- Partners with the Enterprise Architecture practice to ensure AI platform decisions are represented in ARB processes, architecture standards, and the broader technology roadmap.
- Collaborates with IT Governance to develop and maintain AI-specific policies, use case intake processes, and risk classification frameworks, serving as the subject matter expert for AI platform controls.
- Implements and maintains Bedrock Guardrails and Microsoft Purview DLP controls at the AI model boundary, working in alignment with security and compliance teams to meet enterprise policy requirements.
- Produces and maintains platform runbooks, standards documents, and AI-specific governance artifacts in coordination with the Enterprise Architecture practice; ensures these remain current as the platform evolves.
- Manages AI vendor relationships including Microsoft (Copilot) and AWS (Bedrock), tracking roadmap developments and surfacing relevant changes to IT Governance and Enterprise Architecture stakeholders.
- Enablement & Community of Practice
- Leads the internal AI Community of Practice, setting agendas, driving participation, and connecting business use cases to platform capability.
- Drives Microsoft 365 Copilot adoption across business units through structured enablement, measurement frameworks, and feedback loops.
- Mentors and upskills matrixed team members, building internal AI capability through an Explorer → Builder → Lead development pathway.
- Serves as the primary internal resource for AI platform questions, escalations, and new use case scoping.
- Other duties as assigned
Supervision of Others: This is a principal-level individual contributor role with no direct reports. The role exercises matrixed authority over cloud, M365, security, and application team members to execute AI platform workstreams, and may grow into a people-management function as the AI practice scales.
Working Conditions: This is a hybrid role. The majority of time is spent in the office environment utilizing computers, phones, and general office equipment. A portion of time is spent outside the office attending vendor meetings, internal stakeholder sessions, and relevant industry conferences.
Qualifications
Education/Experience:
- Bachelor’s degree in Computer Science, Information Systems, or a related field required, Master’s degree preferred. Equivalent work experience may be substituted for a Bachelor’s Degree.
- 7–10 years of experience in cloud platform engineering, DevOps, or infrastructure operations, with demonstrated progression into senior technical ownership.
- Hands-on production experience with AWS Bedrock — including Agents, Knowledge Bases, and Guardrails — not limited to conceptual or sandbox familiarity.
- Demonstrated capability to deploy and govern Microsoft 365 Copilot in an enterprise environment, including sensitivity label configuration, raph connector setup, and DLP policy integration.
- Proven track record operating as a solo or near-solo platform owner with both build and operate responsibilities.
- Experience delivering AI platform work in a matrixed organization without direct report authority.
- Experience integrating structured and unstructured enterprise data sources into AI platforms, including data warehouses (e.g., Snowflake), SharePoint, relational databases, or operational APIs, preferred.
- AWS certifications: Solutions Architect Professional, ML Specialty, or Security Specialty, preferred.
- Microsoft certifications: Azure AI Engineer Associate or M365 Enterprise Administrator Expert, preferred.
- Experience with enterprise ITSM platforms (ServiceNow or equivalent) for AI use case intake and catalog management.
Skills/Knowledge/Abilities:
- AWS services: Bedrock, S3, Lambda, IAM, VPC/PrivateLink, CloudTrail, KMS, OpenSearch Serverless, including hands-on experience with Anthropic Claude models via the Bedrock API.
- Microsoft 365: Copilot, Entra ID / Azure AD, SharePoint Online, Purview, Conditional Access, including familiarity with Copilot extensibility and alternative model backends such as Anthropic Claude.
- Infrastructure as Code: Terraform or AWS CDK for AI infrastructure deployment and lifecycle management.
- RAG architecture: vector embeddings, chunking strategies, retrieval evaluation, and grounding quality assessment.
- AI security and governance: prompt injection controls, PII redaction, output logging, and RBAC for AI tooling.
- Ability to produce high-quality governance documentation — acceptable use policies, architecture decision records, standards documents — without reliance on a technical writer.
- Strong stakeholder communication skills with demonstrated ability to engage both technical teams and business leadership.
- Change management capability, particularly for driving AI tool adoption with non-technical end users.
- Familiarity with enterprise security frameworks (NIST CSF, SOC 2, or similar) and how AI platform controls map to them, preferred.
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