Principal Technical Product Manager, AI Platform & UX

📍 Job Overview

Job Title: Principal Technical Product Manager, AI Platform & UX

Company: Royal Bank of Canada (RBC)

Location: Toronto, Ontario, Canada

Job Type: Full-time, Regular, Salaried

Category: Product Management / AI Platform Strategy

Date Posted: August 31, 2026

Experience Level: 10+ years

🚀 Role Summary

• Lead the end-to-end product strategy and multi-year roadmap for a critical AI platform and user experience capability area, serving both technical engineering teams and non-technical business users.

• Drive the development and adoption of AI solutions at scale within Canada's largest bank, ensuring reliability, ease of use, and scalability.

• Manage a team of product managers, fostering a culture of iterative delivery, user understanding, and data-driven decision-making.

• Partner closely with engineering, design, and cross-functional stakeholders to define requirements, manage dependencies, and ensure successful delivery of platform capabilities.

• Evaluate strategic build-vs-buy-vs-partner decisions for AI platform tooling to optimize investment and accelerate innovation.

📝 Enhancement Note: This role is pivotal for RBC's AI acceleration efforts, focusing on the foundational platform and user interfaces that enable broader AI adoption. It requires a blend of deep technical understanding, strategic product vision, and strong people leadership within a complex, regulated financial services environment.

📈 Primary Responsibilities

• Own and execute the product strategy and roadmap for the AI platform and user experience, prioritizing based on internal adoption, reliability, and business needs.

• Lead discovery processes and define clear product requirements by translating input from engineering, design, and diverse internal stakeholders.

• Manage portfolio-level prioritization and sequencing of initiatives across the AI platform's roadmap and individual product areas.

• Collaborate with engineering and design leadership on feasibility, scope, and trade-offs, ensuring alignment and commitment to delivery plans.

• Partner with project management to translate prioritized requirements into funded programs of work and oversee product scope throughout the delivery lifecycle.

• Act as the primary product representative to senior leadership, providing updates on the platform's health and strategic direction.

• Engage with internal business and technology stakeholders to understand their needs and ensure the platform effectively supports their AI initiatives.

• Contribute to the definition of value messaging, target user personas, and success metrics for platform launches and ongoing improvements.

• Build, mentor, and lead a team of product managers, guiding them in consistent discovery, prioritization, and delivery practices.

• Foster a culture of iterative development, user-centricity, and data-informed decision-making within the product team.

📝 Enhancement Note: The emphasis on both "developer-facing" and "business-user-facing" experiences indicates a need for a product leader who can bridge technical complexities with intuitive user journeys, a critical differentiator for platform adoption in large enterprises.

🎓 Skills & Qualifications

Education:

• University degree in a technical field such as Computer Science, Engineering, or a related discipline, or equivalent practical experience. Experience:

• 10+ years of progressive product management experience, with a strong emphasis on owning platform, infrastructure, or developer-facing products.

• Proven track record of delivering production AI, Machine Learning (ML), or Large Language Model (LLM) based platform products within an enterprise setting.

• Direct experience with LLM API integration at scale (e.g., Anthropic Claude, OpenAI, Azure OpenAI, or equivalent).

• Demonstrated experience in designing and delivering product experiences tailored for both technical (developers) and non-technical (business) user audiences.

• Experience stepping into a people-leadership role from an individual contributor or lead-level product management position is highly desirable.

• Experience operating in a highly regulated industry, such as financial services, is a plus.

• Experience establishing a net-new function or capability area within a scaling organization is advantageous. Required Skills:

• Product Strategy & Roadmap Development: Ability to define and articulate a compelling multi-year vision and actionable roadmap for complex platform capabilities.

• AI/ML Platform Expertise: Deep understanding of AI/ML concepts, production deployment challenges, and specifically LLM-based platforms and integrations.

• Technical Acumen: Strong foundation in system design, API/gateway patterns (authentication, rate limiting, observability), vector databases, Retrieval-Augmented Generation (RAG) architecture, and data pipelines.

• User Experience Design: Skill in translating complex technical capabilities into simple, usable experiences for diverse user groups.

• Stakeholder Management: Proven ability to engage, influence, and represent product strategy credibly to senior executives and engineering teams.

• Cross-functional Collaboration: Experience partnering effectively with engineering, design, project management, and business stakeholders.

• People Leadership & Mentorship: Capability to build, mentor, and lead a team of product managers, fostering their growth and development.

• Data-Driven Decision Making: Proficiency in defining and tracking success metrics to inform ongoing product prioritization and strategy.

Preferred Skills:

• Experience with Platform-as-a-Product (PaaP) operating models, including internal developer platforms and self-service tooling.

• Experience measuring and improving developer experience (DevEx).

• Familiarity with LLM-based product development, AI agent frameworks, or model evaluation tooling.

• Experience with processes for standing up new functions within large organizations.

📝 Enhancement Note: The requirement for direct LLM API integration experience and familiarity with RAG architecture highlights the cutting-edge nature of this role, demanding hands-on knowledge of current AI technologies within an enterprise context.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Platform Strategy Documentation: Evidence of developing and executing multi-year product strategies for complex technical platforms, including clear articulation of vision, goals, and key initiatives.

• Roadmap Visualization & Prioritization: Examples of detailed product roadmaps, demonstrating prioritization methodologies (e.g., RICE, MoSCoW, value vs. effort) and how they align with broader business objectives.

• Technical Requirements & Specifications: Samples of well-defined product requirements documents (PRDs) or equivalent artifacts that clearly outline functional and non-functional requirements for technical products, including API specifications and system design considerations.

• User Experience Design for Technical & Non-Technical Audiences: Portfolios showcasing how complex technical capabilities were translated into intuitive user interfaces and workflows for diverse user groups, including developers and business users.

• Case Studies on AI/ML Platform Implementation: Detailed case studies illustrating the successful development, deployment, and adoption of AI/ML platform components, highlighting challenges overcome, technical solutions implemented, and measurable impact.

Process Documentation:

• Discovery & Requirements Gathering: Demonstrable processes for conducting user research, stakeholder interviews, and market analysis to identify needs and define product requirements for AI platforms.

• Agile Development & Delivery: Experience with Agile methodologies (Scrum, Kanban) for iterative product development, including backlog management, sprint planning, and continuous delivery practices.

• Cross-Functional Partnership & Alignment: Documentation or case studies detailing how product managers effectively partner with engineering, design, and other functional teams to drive consensus and ensure successful product delivery.

• Metrics Definition & Performance Tracking: Examples of defining key performance indicators (KPIs) for platform adoption, reliability, and user satisfaction, and using this data to inform product decisions and measure ROI.

• Build-vs-Buy-vs-Partner Analysis: Documentation of frameworks or case studies used to evaluate external solutions against internal development efforts for platform tooling.

📝 Enhancement Note: Given the "Principal" level and focus on AI platforms, a portfolio should emphasize strategic thinking, technical depth in AI/ML systems, and proven ability to lead complex, cross-functional initiatives with measurable business outcomes.

💵 Compensation & Benefits

Salary Range:

Based on RBC's typical compensation structures for Principal-level roles in Toronto, and considering the specialized nature of AI Platform Product Management, the estimated annual base salary range is CAD $170,000 - $230,000. This range is subject to variation based on the candidate's specific experience, qualifications, and performance during the interview process.

Benefits:

• Comprehensive Total Rewards Program: Includes bonuses, flexible benefits, and competitive compensation.

• Stock Options: Potential for stock awards or participation in equity plans, aligning employee success with company performance.

• Professional Development: Access to leaders who support development through coaching and management opportunities, and a world-class training program in financial services.

• Health & Wellness: Flexible benefits package often includes health, dental, vision, and wellness programs.

• Retirement Savings: Opportunities for retirement savings plans (e.g., RRSP matching).

• Paid Time Off: Generous vacation days, personal days, and statutory holidays.

• Employee Assistance Program: Confidential support services for employees and their families.

Working Hours:

• Standard full-time work week is 37.5 hours.

• While the role is primarily on-site, RBC often offers flexibility in work arrangements, with potential for hybrid models depending on team needs and business requirements. Specific flexibility details would be discussed during the interview process.

📝 Enhancement Note: The salary estimate is based on industry benchmarks for Principal Product Manager roles in major Canadian financial centers like Toronto, factoring in the specialized AI/ML expertise and leadership responsibilities. Benefits are standard for large financial institutions, emphasizing comprehensive employee support.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking)

Company Size: Large Enterprise (RBC is one of Canada's largest banks, with tens of thousands of employees globally). This scale implies robust processes, significant resources, and complex stakeholder landscapes.

Founded: 1864 (The Bank of Montreal, a predecessor of RBC, was founded in 1864). RBC has a long-standing history and a strong reputation in the financial sector.

Team Structure:

• AI Group: This role is within RBC's AI Group, positioned as the "AI accelerator" for the bank. This suggests a central, strategic function focused on driving AI adoption and innovation across the organization.

• Reporting Structure: The Principal Technical Product Manager will report to a senior leader within the AI Group and will, in turn, lead a team of Product Managers focused on the AI Platform and User Experience.

This indicates a hierarchical structure with clear lines of responsibility.

• Cross-functional Collaboration: The role necessitates extensive collaboration with various internal teams, including:
  • Engineering: To build and scale the AI platform.
  • Design: To ensure user-centric experiences for both technical and non-technical users.
  • Business Units: To understand adoption needs and ensure value delivery.
  • Architecture & Governance: To ensure compliance and alignment with enterprise standards.
  • Go-to-Market Peers: To ensure successful launch and adoption strategies.

Methodology:

• Data-Driven AI Development: The AI Group focuses on translating AI projects into "scaled, client outcomes," emphasizing measurable impact and data-informed decision-making.

• Iterative Delivery: The role fosters a culture of "iterative delivery," aligning with Agile principles to ensure continuous improvement and responsiveness to user needs.

• Responsible AI & Governance: Given the financial services context, there's an implicit focus on responsible AI practices, security, and adherence to regulatory expectations.

• Strategic Planning: The role requires long-term strategic planning for platform capabilities, balancing internal investment against external solutions.

Company Website: https://jobs.rbc.com/ca/en

📝 Enhancement Note: RBC's position as a major financial institution means operations within the AI Group must adhere to strict regulatory compliance, security protocols, and risk management frameworks, which will influence platform design and user experience.

📈 Career & Growth Analysis

Operations Career Level: Principal Technical Product Manager. This is a senior individual contributor or leadership role, typically one or two levels below Director/VP. It signifies ownership of a significant, strategic product area with substantial impact and responsibility for guiding other product managers. In the context of AI platforms, this level implies deep technical expertise combined with strategic product vision and leadership capabilities.

Reporting Structure: The role reports into senior leadership within the AI Group and directly manages a team of Product Managers. This structure provides a clear path for guidance from senior leadership and an opportunity to develop leadership skills through managing a team. The emphasis on partnering with adjacent product and engineering leaders suggests a highly collaborative, matrixed environment common in large tech and financial organizations.

Operations Impact: The impact of this role is substantial, directly influencing RBC's ability to scale AI solutions across the enterprise. By owning the core AI platform and UX, this role enables other business units to innovate faster, improve operational efficiency, enhance client experiences, and drive new revenue streams through AI. Success here directly translates to competitive advantage for RBC in the financial services landscape.

Growth Opportunities:

• Leadership Expansion: Potential to grow into a Director-level role overseeing a larger product portfolio or multiple AI capability areas.

• Strategic Influence: Opportunity to shape the long-term AI strategy for one of Canada's largest banks, influencing major technology investments and business transformations.

• Specialization: Deepen expertise in cutting-edge AI technologies (Generative AI, Agentic AI, LLMs) within a regulated financial services context, becoming a recognized expert.

• Cross-Functional Leadership: Develop broader leadership skills by collaborating with and influencing senior stakeholders across technology, business, legal, and compliance functions.

• Mentorship & Team Development: Hone people management and coaching skills by mentoring and developing a team of product managers.

📝 Enhancement Note: The "Principal" title and the focus on a foundational AI platform indicate that this role is critical for RBC's future technological direction. Growth opportunities are likely tied to the successful scaling of AI initiatives and the candidate's ability to demonstrate strategic leadership and impact.

🌐 Work Environment

Office Type: RBC Waterpark Place, 88 Queens Quay West, Toronto. This is a modern, large corporate office building located in Toronto's waterfront business district. It is designed to foster collaboration and efficiency.

Office Location(s): Primarily based at RBC Waterpark Place in Toronto, Ontario. This location is a central hub for many RBC operations, offering access to extensive resources and networking opportunities.

Workspace Context:

• Collaborative Environment: The office space is likely designed to encourage interaction, with open work areas, meeting rooms, and collaborative zones. This supports the role's need for constant interaction with engineering, design, and business stakeholders.

• Technology & Tools: As a Principal Technical Product Manager, access to advanced technology infrastructure, development tools, and communication platforms is expected. This would include high-performance computing resources for AI development, robust collaboration software, and efficient data analytics tools.

• Team Interaction: The role involves regular interaction with a dedicated AI Group, including product managers, engineers, designers, data scientists, and AI strategists. This provides a rich ecosystem for knowledge sharing and problem-solving.

Work Schedule:

• The standard work schedule is 37.5 hours per week, with a primary focus on on-site presence at the Toronto office.

• While full-time on-site is the default, large organizations like RBC often have policies that allow for hybrid work arrangements for certain roles, especially at senior levels, subject to business needs and team agreements. This would be a point of discussion during the interview process.

📝 Enhancement Note: The emphasis on an on-site presence in a major corporate hub like RBC Waterpark Place suggests a structured work environment where face-to-face collaboration and integration with the broader RBC technology and business ecosystem are highly valued.

📄 Application & Portfolio Review Process

Interview Process:

1. Initial Screening: Recruiter or hiring manager will review your resume and cover letter for alignment with the must-have qualifications.

2. Hiring Manager/Team Interview: A discussion focused on your experience with AI platforms, product strategy, technical depth, and people leadership. Expect questions about your approach to product roadmapping, stakeholder management, and team mentorship.

3. Technical Deep Dive: An interview with engineering and architecture leads to assess your technical understanding of AI/ML platforms, system design, API patterns, and LLM technologies. Be prepared to discuss technical trade-offs and architectural considerations.

4. Product Strategy & Case Study Presentation: You will likely be asked to present a case study from your portfolio, demonstrating your ability to define strategy, drive product development, and deliver impact for a technical platform or AI-related product. This may involve a prepared presentation or a live problem-solving exercise.

5. Cross-Functional Stakeholder Interviews: Meetings with key business and technology stakeholders to evaluate your communication, collaboration, and alignment skills across different organizational functions.

6. Final Round / Executive Interview: A discussion with senior leadership to assess strategic fit, leadership potential, and overall alignment with RBC's culture and values.

Portfolio Review Tips:

• Showcase Platform Ownership: Highlight projects where you owned the strategy, roadmap, and execution for a complex technical platform or infrastructure product.

• Quantify AI/ML Impact: For AI/ML projects, clearly articulate the business problem, the technical solution (including specific AI/ML models or LLM integrations), the challenges faced, and measurable outcomes (e.g., adoption rates, efficiency gains, revenue impact, cost savings).

• Demonstrate Technical Depth: Include examples that showcase your understanding of system architecture, API design, data pipelines, and relevant AI technologies (LLMs, RAG, vector databases).

• Illustrate User Experience Design: Provide examples of how you translated complex technical capabilities into intuitive experiences for both developers and non-technical users.

• Highlight Leadership & Collaboration: Include projects that demonstrate your ability to lead product teams, mentor junior colleagues, and collaborate effectively with diverse cross-functional teams.

• Tailor to RBC: Research RBC's AI initiatives and strategic priorities. Frame your portfolio examples to show how your experience directly addresses their needs and challenges.

Challenge Preparation:

• AI Platform Strategy: Be ready to discuss how you would approach developing a product strategy for an enterprise AI platform, considering factors like scalability, security, cost, and user adoption.

• Technical Problem Solving: Prepare for scenarios where you might need to diagnose issues with AI model performance, API integrations, or platform scalability.

• Stakeholder Alignment: Practice articulating complex technical concepts and product strategies to both technical and non-technical audiences, demonstrating your ability to drive consensus.

• People Management Scenarios: Be prepared to discuss your leadership philosophy, how you mentor product managers, and how you handle team performance issues.

📝 Enhancement Note: The emphasis on a "Principal Technical Product Manager" role suggests that a significant portion of the interview process will focus on strategic thinking, deep technical understanding of AI platforms, and leadership capabilities, with a portfolio that clearly demonstrates these aspects.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management Platforms: Jira, Confluence, Aha!, Productboard, or similar for backlog management, roadmap planning, and documentation.

• Collaboration Suites: Microsoft Teams, Slack, Google Workspace for daily communication and team collaboration.

• Diagramming & Prototyping: Lucidchart, Miro, Figma, Sketch for visualizing system architecture, workflows, and user interfaces.

Analytics & Reporting:

• Data Visualization Tools: Tableau, Power BI, Looker for creating dashboards and reporting on platform performance, user adoption, and key metrics.

• Web/Product Analytics: Google Analytics, Adobe Analytics, Pendo for tracking user behavior and feature adoption.

• Business Intelligence (BI) Tools: For aggregating and analyzing data from various sources to inform strategic decisions.

CRM & Automation:

• CRM Systems: While not directly managing a sales CRM, understanding of how AI platforms integrate with or support CRM functionalities is beneficial.

• Workflow Automation: Tools related to CI/CD pipelines, infrastructure-as-code, or internal workflow automation platforms used in a large enterprise.

• API Management Platforms: For managing, securing, and monitoring APIs critical to the AI platform.

AI/ML Specific Technologies (Expected Proficiency/Familiarity):

• LLM APIs: Direct experience with Anthropic Claude, OpenAI (GPT-x), Azure OpenAI, or equivalent.

• Vector Databases: Understanding of Pinecone, Weaviate, Milvus, ChromaDB, or similar for semantic search and RAG.

• RAG Architecture: Proficiency in designing and implementing Retrieval-Augmented Generation patterns.

• Cloud Platforms: Experience with major cloud providers (AWS, Azure, GCP) and their AI/ML services.

• MLOps Tools: Familiarity with tools for model training, deployment, monitoring, and management (e.g., MLflow, Kubeflow, SageMaker).

• Data Pipeline Tools: Experience with tools for ETL/ELT, data warehousing, and data orchestration.

📝 Enhancement Note: Proficiency in AI/ML-specific technologies, especially LLM APIs and RAG architecture, is a core requirement. Experience with enterprise-grade collaboration, project management, and data visualization tools is also crucial for success in this role.

👥 Team Culture & Values

Operations Values:

• Client First: Prioritizing the needs and success of internal business users and ultimately external clients in all platform development and UX decisions.

• Integrity: Upholding ethical standards in AI development and deployment, ensuring responsible AI practices, data privacy, and compliance with financial regulations.

• Collaboration: Fostering a highly collaborative environment, working seamlessly across engineering, design, business units, and other stakeholders to achieve shared goals.

• Respect: Valuing diverse perspectives, fostering an inclusive environment where all team members feel heard and respected, and promoting mutual understanding.

• Excellence: Driving for high standards in platform reliability, performance, scalability, and user experience, continuously seeking opportunities for improvement and innovation.

Collaboration Style:

• Cross-Functional Integration: The team operates with a strong emphasis on integrating product management, engineering, and design early and continuously throughout the product lifecycle.

• Process Review & Feedback: A culture of open feedback and iterative process refinement is encouraged, where team members regularly review their workflows and seek ways to improve efficiency and effectiveness.

• Knowledge Sharing: The team actively shares insights, best practices, and learnings, particularly around complex AI technologies and platform development, often through internal demos, documentation, and discussions.

• Data-Informed Experimentation: A willingness to experiment with new approaches and technologies, using data to validate hypotheses and drive product direction.

📝 Enhancement Note: RBC's stated values (Client First, Integrity, Collaboration, Respect, Excellence) are deeply embedded in its culture. Operations professionals are expected to embody these values in their daily work, particularly Integrity given the financial sector's regulatory environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Scaling AI in a Regulated Environment: Navigating the complexities of deploying advanced AI technologies within a highly regulated financial services industry, balancing innovation with strict compliance, security, and risk management requirements.

• Bridging Technical & Business Audiences: Effectively translating complex AI platform capabilities into tangible business value and intuitive user experiences for both highly technical developers and non-technical business users.

• Managing Dependencies: Coordinating efforts across numerous internal teams and potentially external vendors to ensure seamless integration and consistent delivery of platform components.

• Rapidly Evolving AI Landscape: Keeping pace with the fast-moving advancements in AI, ML, and LLM technologies, and strategically integrating them into the platform roadmap while ensuring stability and reliability.

• Driving Adoption: Overcoming potential organizational inertia and encouraging widespread adoption of the AI platform by demonstrating clear value, providing excellent user experiences, and offering robust support.

Learning & Development Opportunities:

• AI/ML Specialization: Deepen expertise in cutting-edge areas like Generative AI, Agentic AI, LLM orchestration, and MLOps through hands-on project work, internal training, and potential external certifications.

• Leadership Development: Gain extensive experience in people management, strategic planning, and cross-functional leadership within a large, complex organization.

• Industry Exposure: Benefit from RBC's world-class training programs and potential opportunities to attend industry conferences and workshops focused on AI, product management, and financial technology.

• Mentorship: Receive guidance from senior leaders within RBC's AI Group and potentially from executive mentors, offering invaluable career advice and strategic insights.

• Cross-Functional Acumen: Develop a broad understanding of various business functions within a major bank, enhancing your ability to connect technology solutions to diverse business needs.

📝 Enhancement Note: The challenges presented are typical for senior roles in AI within enterprise settings, especially in finance. Growth opportunities are significant, offering a path to becoming a leader in AI product strategy within a highly reputable financial institution.

💡 Interview Preparation

Strategy Questions:

• "Describe your approach to developing a multi-year product strategy for a complex technical platform like an AI platform. How would you balance innovation with stability and scalability?"

• "How would you prioritize features for an AI platform that serves both developers and business users? What frameworks or methodologies would you use?"

• "Imagine we are considering building a new LLM-based feature versus buying a third-party solution. Walk us through your decision-making process."

• "How do you define and measure success for a platform product, particularly one focused on AI adoption and developer productivity?" Company & Culture Questions:

• "What interests you most about RBC and our AI initiatives?"

• "How do you embody RBC's values (Client First, Integrity, Collaboration, Respect, Excellence) in your work as a product manager?"

• "Describe your experience working in a regulated industry. What are the key considerations for product development in such an environment?"

• "How would you foster a culture of data-driven decision-making and iterative delivery within your product team?" Portfolio Presentation Strategy:

• Structure: For each case study, follow a clear narrative: Problem (business need/user pain point), Solution (your strategy, product features, technical approach), Execution (how you partnered with teams, overcame challenges), and Results (quantifiable impact, lessons learned).

• Technical Detail: Clearly articulate the technical aspects of your AI/ML platform projects, including the architecture, LLM integrations, data flows, and any specific challenges related to AI deployment.

• User Focus: Emphasize how you designed the user experience for both technical and non-technical users, showcasing user research, personas, and UX design principles.

• Quantifiable Impact: Use data and metrics relentlessly to demonstrate the value and ROI of your work. For platform products, focus on adoption rates, efficiency gains, cost savings, or revenue enablement.

• Leadership & Collaboration: Highlight your role in leading teams, influencing stakeholders, and driving cross-functional alignment.

📝 Enhancement Note: Prepare to discuss not only your past successes but also how you approach ambiguity, navigate complex stakeholder landscapes, and drive technical innovation within strict operational and regulatory frameworks, which are critical for this role at RBC.

📌 Application Steps

To apply for this Principal Technical Product Manager position at RBC:

• Submit your application: Utilize the provided application link on the RBC jobs portal. Ensure your application is submitted well before the deadline of September 30, 2026.

• Tailor your Resume: Customize your resume to highlight your 10+ years of product management experience, specifically emphasizing your work with AI/ML platforms, LLM integrations, developer-facing products, and people leadership. Use keywords from the job description and integrate quantifiable achievements.

• Curate Your Portfolio: Prepare a concise and impactful portfolio that showcases your strategic thinking, technical depth, user experience design for diverse audiences, and leadership capabilities. Focus on AI/ML platform projects with clear, measurable business outcomes.

• Prepare for Interviews: Thoroughly research RBC's AI strategy, company values, and the financial services industry. Practice answering strategy, technical, and behavioral questions, and prepare a compelling presentation for any case study or portfolio review requirements.

• Network (Optional but Recommended): If possible, connect with current RBC employees in product management or AI roles on LinkedIn to gain insights into the company culture and team dynamics.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.