Posted today · be early
Senior Manager, AI & Enterprise Architecture
ST Engineering iDirect
WorldwideremotePosted today
Skill Required
AI-ArchitectureSolutions-ArchitectAI-Platform-EngineeringAI-ML-EngineerTechnology-LeadershipSenior-Enterprise-Architecture-ManagerSenior-AI-ArchitectSenior-IT-Enterprise-ArchitectSenior-AI-Adoption-ArchitectSenior-AI-and-Analytics-ManagerSenior-Manager-In-AISenior-Enterprise-Business-ArchitectDirector-of-Data-and-AI-ArchitectureAIDesign Patternsrelated fieldPrototypingEngineeringSalesforceautomationUnreal EngineJiradesigningdebugginganalyticssecuritybuildingetc.)designDevOpsAzureCloudAPIsGenerative AISAPandETLMachine LearningFulltime
Key highlights
- 8–12+ years of experience required
- Player-coach role expected to personally deliver and build solutions, not just direct teams
- Must have hands-on experience building production-grade solutions (not just designing)
- Degree in Computer Science, Engineering, or related field required
- Azure cloud experience preferred
- Will lead the Architecture Review Board (ARB)
Role overview
At ST Engineering iDirect, the Senior Manager, AI & Enterprise Architecture drives 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.
Responsibilities
- Design, build, and deploy AI-driven and automation solutions across business processes
- Develop and implement use cases such as bid management automation, financial reporting optimization, and Salesforce and customer workflow enhancements
- Build solutions using AI platforms (Copilot, Dataiku, LLM-based services), workflow automation/orchestration tools, APIs, and integration layers
- Actively contribute to prototyping, development, and solution debugging
- Drive rapid delivery of high-impact use cases from POC to production; personally deliver and unblock critical solutions, not just direct teams
- Define and evolve the enterprise AI platform architecture, including unified data fabric, AI orchestration layer, and API-first integration strategies
- Translate business needs into end-to-end solution architectures and blueprints
- Establish and enforce architecture principles, design patterns, and best practices
- Ensure solutions are scalable and reusable, secure and compliant, and built on shared platforms rather than siloed tools
- Partner with business stakeholders to translate prioritized initiatives into implementable solutions
- Ensure all work ties directly to measurable KPIs: cycle time reduction, cost savings, productivity gains, and CSAT/revenue impact
- Provide technical leadership on high-priority Business Excellence initiatives
- Establish and lead Architecture Review Board (ARB)
- Enforce use of approved platforms, reusable components, and standardized integration patterns
- Prevent tool proliferation and fragmented AI adoption; drive consolidation into a centralized AI platform model
- Design and implement architecture across core enterprise systems: Salesforce, SAP/Finance systems, Jira/Confluence
- Build and guide API integrations, event-driven workflows, data pipelines, and AI data layers
- Enable cross-system intelligence and automation at scale
- Create reusable assets including solution templates, architecture patterns, and AI/automation components
- Standardize solution delivery to reduce time-to-solution and integration complexity
- Act as a hands-on escalation point for complex technical challenges
- Ensure all solutions meet standards for scalability, security, maintainability, and cost efficiency
- Balance speed vs architectural integrity; reduce long-term technical debt while enabling fast execution
- Act as the technical bridge between business, ELT, and engineering teams
- Influence prioritization using value vs effort and architectural tradeoffs
- Drive alignment across Business Excellence, AI, DevOps, and IT functions
- Ensure strong adoption and real business impact of delivered solutions
- Operate across architecture → build → scale, ensuring what is designed is also successfully implemented and adopted
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field
- 8–12+ years in enterprise technology, solution architecture, or platform engineering
- Proven experience building and delivering production-grade solutions (not just designing)
- Experience leading architecture direction while remaining hands-on
- Strong hands-on experience with AI/ML platforms (LLMs, copilots, AI services)
- Strong hands-on experience with automation frameworks and orchestration tools
- Strong hands-on experience with API and integration development
- Understanding of security, governance, and compliance in AI systems
- Understanding of DevOps/DevSecOps practices
Nice to have
- Experience with cloud platforms (Azure preferred)
- Experience with data pipelines and analytics platforms
- Experience with enterprise systems such as Salesforce and ERP
Additional details
- Key characteristics of success include: player-coach mindset (leads by building, not just directing), strong ability to move from idea to architecture to working solution to scale, bias toward execution and measurable outcomes, ability to enforce standards without slowing delivery, strong systems thinking across process/data/technology, and comfort operating in ambiguity and driving clarity
- 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
- Originally posted on Himalayas
