Senior Manager AI Platform Architecture

Senior Manager AI Platform Architecture

Use your skills where innovative technology solutions begin. ECLARO is looking for a Senior Manager AI Platform Architecture for our client in Bolingbrook, IL. ECLARO's client is a leading technology solutions provider, collaborating with customers to manage their needs and achieve success in their business goals. If you're up to the challenge, then take a chance at this rewarding opportunity!

Position Overview:

• The Senior Manager, AI Platform Architecture is a hands-on leader responsible for the architecture and evolution of our core AI platforms.
• In this role, will manage a team of skilled engineers and architects, collaborate with cross-functional stakeholders, and help set the strategic direction of platform architecture to ensure scalability, performance, and reliability across our systems.
• The expertise in platform architecture, cloud technologies, automation, and AIML Ops practices will be critical in driving our strategy and ensuring the reliability and efficiency of our systems.

Responsibilities:

• Strategic Platform Leadership:
• Translate enterprise AI strategy defined by the AI Architect Principal, Enterprise Architecture, Enterprise AI Tech Leaders (AI Engineering, DS / ML Engineering, AI Emerging Tech), AI Product Teams into actionable platform roadmaps and technical priorities.
• Partner with data, cloud, security, and infrastructure teams to define the end-to-end AI architecture framework, including compute, model lifecycle, and deployment strategies.
• Evaluate emerging technologies and recommend platform enhancements to improve model performance, scalability, and sustainability.
• Define and deliver AI / ML / Agentic operations strategy – including tool suite, standards, and technology / capability roadmap.
• Establish POV on key evaluations – including, but not limited to "buy v. build", platform assessments, tool comparisons, cost / performance optimizations.
• Drive the technical strategy for the platform, balancing short-term needs with long-term scalability and reliability.
• Design, implement, and scale cloud-based infrastructures (GCP and Databricks) to support internal and external applications.
• Oversee platform architecture decisions, ensuring that the platform is robust, efficient, and capable of supporting growing business needs.
• Architecture Design and Governance:
• Lead the design of core AIML platform components—data pipelines, model training and inference engines, orchestration workflows, and monitoring frameworks.
• Design for continuous training pipelines and promote automation capabilities where possible.
• Establish architectural best practices, patterns, and standards for AI / ML development and deployment.
• Oversee design reviews and ensure compliance with enterprise architecture and regulatory requirements.
• Design and build platform to meet AI Governance requirements (including application of controls and measurement of controls). Ensure observability requirements can be met.
• Cross-Functional Collaboration:
• Work closely with product, data science, engineering, and security teams to operationalize AI / ML capabilities across the enterprise.
• Partner with the AI Architect Principal and AI Solution Architects to align agentic platform evolution with organizational priorities and technology roadmaps.
• Collaborate with security and operations teams to ensure the platform is secure, compliant, and maintains high uptime and reliability.
• Engage with leadership to align technical initiatives with organizational objectives.
• Team Leadership and Talent Development:
• Manage and mentor a team of AI engineers, AI architects, and AI Ops engineers.
• Foster a high-performance culture emphasizing innovation, collaboration, and agile delivery.
• Support career development, technical upskilling, and diversity in AI technology roles, specifically those aligned into the Architecture space. Mentor and guide junior team members.
• Conduct regular performance reviews, provide career development guidance, and support team members' growth and skill development.
• Own hiring, onboarding, and team-building activities to ensure the team has the right talent and skills.
• Provide hands-on technical leadership, leading by example in designing and building robust, scalable systems.
• Drive high standards of code quality, testing, and engineering practices.
• Advocate for platform engineering best practices, ensuring systems are maintainable, extensible, and documented.
• Operational Excellence:
• Oversee platform scalability, reliability, and cost optimization across cloud and on-prem environments.
• Implement observability and monitoring tools to proactively identify performance or security issues.
• Ensure platform compliance with responsible AI, data privacy, and ethical ML principles.
• Build and develop architecture audit process, and execute.
• Identify opportunities for automation, process improvements, and tooling that enhance platform reliability and efficiency.
• Stay current with emerging technologies and industry best practices and…