Senior Manager, AI & Enterprise Architecture

OverviewAt ST Engineering iDirect, the Senior Manager, AI & Enterprise Architecture is responsible for driving the technical realization of iDirect’s AI-powered Business Excellence transformation through a combination of hands-on execution and architectural leadership.Reporting to the VP, Technology & Information Security, this role defines architectural direction while actively building and delivering AI-enabled solutions, integrations, and platform capabilities that reduce manual effort, improve decision-making, and accelerate time-to-value.This is a player-coach role requiring both deep technical execution and the ability to set standards, guide architecture, and scale solutions across the enterprise.Role SummaryThis role owns both the design and delivery of AI-enabled solutions and enterprise architecture, ensuring business initiatives are translated into scalable, reusable, and measurable outcomes.Key focus areas include:Enterprise AI platform architecture and solution designHands-on development and deployment of AI/automation solutionsBusiness-driven solutioning tied to measurable outcomesPlatform standardization and reuseIntegration, data, and orchestration architectureThe role operates across architecture → build → scale, ensuring that what is designed is also successfully implemented and adopted.Responsibilities

Key Responsibilities

Hands-On AI Solution Delivery (Core Expectation)Design, build, and deploy AI-driven and automation solutions across business processesDevelop and implement use cases such as: Bid management automationFinancial reporting optimizationSalesforce and customer workflow enhancementsBuild solutions using: AI platforms (Copilot, Dataiku, LLM-based services)Workflow automation / orchestration toolsAPIs and integration layersActively contribute to prototyping, development, and solution debuggingDrive rapid delivery of high-impact use cases (POC → production)This role is expected to personally deliver and unblock critical solutions, not just direct teamsEnterprise Architecture & Solution DesignDefine and evolve the enterprise AI platform architecture, including: Unified data fabricAI orchestration layerAPI-first integration strategiesTranslate business needs into end-to-end solution architectures and blueprintsEstablish and enforce architecture principles, design patterns, and best practicesEnsure solutions are: Scalable and reusableSecure and compliantBuilt on shared platforms (not siloed tools)Business-Driven SolutioningPartner with business stakeholders to translate prioritized initiatives into implementable solutionsEnsure all work ties directly to measurable KPIs: Cycle time reductionCost savingsProductivity gainsCSAT / revenue impactProvide technical leadership on high-priority Business Excellence initiativesAI Platform Governance & StandardizationEstablish and lead Architecture Review Board (ARB)Enforce use of: Approved platformsReusable componentsStandardized integration patternsPrevent tool proliferation and fragmented AI adoptionDrive consolidation into a centralized AI platform modelData, Integration & Platform EngineeringDesign and implement architecture across core enterprise systems: SalesforceSAP / Finance systemsJira / ConfluenceBuild and guide: API integrationsEvent-driven workflowsData pipelines and AI data layersEnable cross-system intelligence and automation at scaleDelivery Acceleration & EnablementCreate reusable assets including: Solution templatesArchitecture patternsAI and automation componentsStandardize solution delivery to reduce: Time-to-solutionIntegration complexityAct as a hands-on escalation point for complex technical challengesTechnology Governance & QualityEnsure all solutions meet standards for: ScalabilitySecurityMaintainabilityCost efficiencyBalance speed vs architectural integrityReduce long-term technical debt while enabling fast executionCross-Functional LeadershipAct as the technical bridge between business, ELT, and engineering teamsInfluence prioritization using: Value vs effortArchitectural tradeoffsDrive alignment across Business Excellence, AI, DevOps, and IT functionsEnsure strong adoption and real business impact of delivered solutions

Qualifications

Qualifications

ExperienceBachelor’s degree in Computer Science, Engineering, or related field8 - 12+ years in enterprise technology, solution architecture, or platform engineeringProven experience building and delivering production-grade solutions (not just designing)Experience leading architecture direction while remaining hands-onTechnical ExpertiseStrong hands-on experience with: AI/ML platforms (LLMs, copilots, AI services)Automation frameworks and orchestration toolsAPI and integration developmentExperience with: Cloud platforms (Azure preferred)Data pipelines and analytics platformsEnterprise systems (Salesforce, ERP, etc.)Understanding of: Security, governance, and compliance in AI systemsDevOps / DevSecOps practicesKey Characteristics of SuccessPlayer-coach mindset: leads by building, not just directingStrong ability to move from idea → architecture → working solution → scaleBias toward execution and measurable outcomesAbility to enforce standards without slowing deliveryStrong systems thinking across process, data, and technologyComfortable operating in ambiguity and driving clarityOriginally posted on Himalayas