[Hiring] Senior Manager, AI & Enterprise Architecture @ST Engineering iDirect

Role Description

At 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.

Responsibilities

• Hands-On AI Solution Delivery (Core Expectation)
  • 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
    • 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 (POC → production).
  • This role is expected to personally deliver and unblock critical solutions, not just direct teams.
• Enterprise Architecture & Solution Design
  • Define and evolve the enterprise AI platform architecture, including:
    • Unified data fabric
    • AI orchestration layer
    • 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
    • Built on shared platforms (not siloed tools)
• Business-Driven Solutioning
  • 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
    • CSAT / revenue impact
  • Provide technical leadership on high-priority Business Excellence initiatives.
• AI Platform Governance & Standardization
  • Establish and lead Architecture Review Board (ARB).
  • Enforce use of:
    • Approved platforms
    • Reusable components
    • Standardized integration patterns
  • Prevent tool proliferation and fragmented AI adoption.
  • Drive consolidation into a centralized AI platform model.
• Data, Integration & Platform Engineering
  • 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.
• Delivery Acceleration & Enablement
  • Create reusable assets including:
    • Solution templates
    • Architecture patterns
    • AI and automation components
  • Standardize solution delivery to reduce:
    • Time-to-solution
    • Integration complexity
  • Act as a hands-on escalation point for complex technical challenges.
• Technology Governance & Quality
  • Ensure all solutions meet standards for:
    • Scalability
    • Security
    • Maintainability
    • Cost efficiency
  • Balance speed vs architectural integrity.
  • Reduce long-term technical debt while enabling fast execution.
• Cross-Functional Leadership
  • Act as the technical bridge between business, ELT, and engineering teams.
  • Influence prioritization using:
    • Value vs effort
    • Architectural tradeoffs
  • Drive alignment across Business Excellence, AI, DevOps, and IT functions.
  • Ensure strong adoption and real business impact of delivered solutions.

Qualifications

• 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)
  • Automation frameworks and orchestration tools
  • API and integration development
• Experience with:
  • Cloud platforms (Azure preferred)
  • Data pipelines and analytics platforms
  • Enterprise systems (Salesforce, ERP, etc.)
• Understanding of:
  • Security, governance, and compliance in AI systems
  • DevOps / DevSecOps practices

Key Characteristics of Success

• Player-coach mindset: leads by building, not just directing.
• Strong ability to move from idea → architecture → working solution → scale.
• Bias toward execution and measurable outcomes.
• Ability to enforce standards without slowing delivery.
• Strong systems thinking across process, data, and technology.
• Comfortable operating in ambiguity and driving clarity.