Job Description We are seeking a Senior IT platform professional to act as the AI & Data Platform Owner within DIGITALcore responsible for the vision, roadmap, and hands‑on delivery of GDMS’ secure AI, GenAI, and data platform capabilities in AWS. You will build "paved roads" that enable GDMS programs and internal teams to deploy AI/ML and data workloads quickly, securely, and repeatably, aligned to regulated‑environment requirements.This role blends deep platform and infrastructure expertise with service ownership thinking. You will own the platform backlog, define reference architectures, lead implementation, and ensure operational excellence. The ideal candidate is customer‑obsessed and UX‑minded, able to translate real user workflows into secure, intuitive IT platform experiences.Key Responsibilities AI & Data Platform OwnershipOwn the AI & Data platform roadmap inside DIGITALcore: define priorities, epics, and release plans for GenAI, ML, and data foundations in AWS.Establish platform outcomes and metrics: onboarding speed, model deployment cycle time, reliability, security posture, cost efficiency, and user satisfaction.Align priorities with DIGITALcore governance, enterprise architecture, security/compliance, and program delivery needs.GenAI Platform (Amazon Bedrock)Lead the secure deployment and operationalization of Amazon Bedrock capabilities (model access, guardrails, logging, governance, and cost controls).Build reusable patterns for GenAI applications: prompt management, RAG patterns, embeddings, evaluation, and production‑grade integration patterns.Drive implementation and adoption of Bedrock AgentCore and Strands for agentic workflows, orchestration patterns, tools/functions, and safe execution in a controlled environment.Define "secure GenAI paved roads" including identity/access patterns, data access boundaries, network controls, and auditability.ML Platform & MLOps (Amazon SageMaker)Lead the deployment of GDMS’ MLOps capability using Amazon SageMaker and related AWS services.Establish standard pipelines for training, evaluation, model registry, approval gates, packaging, deployment, monitoring, and rollback.Implement and maintain reference architectures for:Feature engineering and feature store patterns (as applicable)Model training workflows (batch/stream)Real‑time and batch inference architecturesModel monitoring (drift, bias, performance) and retraining triggersEnable program teams with templates, starter kits, and repeatable CI/CD patterns for ML workloads.Data Platform FoundationsDefine and evolve secure data platform patterns under DIGITALcore: data ingestion, storage, cataloging, governance, and access controls.Build secure, compliant data access patterns to support analytics and AI workloads (including data classification handling and least‑privilege access).Ensure alignment with enterprise logging, monitoring, and audit evidence requirements for data movement and model usage.Secure Cloud Construct & Compliance EnablementOperate within DIGITALcore’s secure landing zone constraints: segmentation, encryption, identity controls, logging, and evidence generation.Translate regulated‑environment requirements into platform guardrails and automation (secure‑by‑default architectures).Build audit‑ready artifacts: standard configs, platform runbooks, automated checks, control mappings, and evidence packages.Operational Excellence & Customer ExperienceOwn platform reliability: SLOs, incident management, change control, and operational runbooks.Treat internal users as customers: conduct user discovery, map workflows, reduce friction, and improve "time‑to‑first‑model" and "time‑to‑first‑agent".Improve usability with clear docs, onboarding paths, templates, and opinionated "golden paths" that teams can follow safely.Cross‑Functional LeadershipPartner with security, architecture, and program engineering teams to ensure platform capabilities meet mission needs.Influence standards for AI governance (usage monitoring, guardrails, model approval gates, and lifecycle controls).Qualifications Required Qualifications7+ years in software, platform, data, or machine learning technical roles, with 3+ years delivering AWS‑based platforms at scale. Deep hands‑on experience with Amazon Bedrock, including secure deployment patterns and operational governance.Working knowledge of Bedrock AgentCore and Strands, including agentic design patterns and tool integration.Strong experience with Amazon SageMaker and the ability to lead the deployment of a production‑grade MLOps capability.Proven ability to design secure architectures in regulated environments: encryption/KMS, IAM least privilege, network boundaries, and centralized logging.Experience with Infrastructure as Code and CI/CD automation for platform delivery.Demonstrated ability to lead delivery through cross‑functional teams (and vendors/partners if applicable).Preferred QualificationsAWS Machine Learning Specialty and/or Solutions Architect Professional.Experience with data governance and cataloging patterns (e.g., metadata management, lineage, access controls).Experience with GenAI evaluation frameworks, safety testing, red teaming, and prompt/version governance.Experience with IT service ownership, platform lifecycle management, or service delivery models.Familiarity with SOC/SIEM integration patterns for AI and data telemetry (who did what, when, and with what data/model).Compensation & Benefits Salary:$95,000 - $130,000 CAD Annual.The expected salary range is based on qualifications, experience, technical and non‑technical skills, education and certifications, and internal equity.Benefits:Comprehensive medical, dental and vision coverage for you and your eligible dependents, from day one at no cost to you.Flexible benefit options including HCSA.Emergency medical travel insurance.24/7 virtual health care services.Employee & Family Assistance Program (EFAP) – counselling, life coaching, lifestyle change support, and financial planning.Onsite fitness facilities and employee resource groups.Defined Contribution Pension Plan (DCPP) with employer contributions after 3 months of service.Access to financial advisors for investment advice and comprehensive financial planning.Voluntary Registered Retirement Savings Plan (RRSP) accessible from day one.Flexible time away: vacation, holidays, vacation purchase plan and parental leaves (with top‑up options).Sick leave and disability programs.Free access to a learning platform offering a wide range of courses and resources.Educational Assistance Program to support formal learning.Self‑directed mentoring opportunities.Reimbursement for professional and industry‑related memberships and dues.Employee discounts on travel, home and auto insurance, and other services and activities.Free onsite parking.Annual scholarship program for children of GD employees.Employee social clubs and recreational activities.Accommodation If you require accommodation during any stage of the application process, please contact Human Resources via Application Closing Policy We reserve the right to close this vacancy early if we receive sufficient applications for the role. Therefore, if you are interested, please submit your application as early as possible.#J-18808-Ljbffr