Senior Infrastructure Solutions Engineering (AI & Automation)

We work as trusted business partners and always strive to deliver the most value and highest return on investment for our clients. We are highly trained business professionals with a strong understanding of clients' needs. We work closely with the leading staffing trade associations, training, and research organizations to ensure we are knowledgeable of the latest industry trends and technologies.

Overview
Our client is seeking a highly experienced Senior Vice President, Infrastructure Solutions Engineering leader to drive the next generation of AI-powered infrastructure automation across the enterprise. This individual will lead a major transformation initiative focused on automating Level 1 support operations through conversational AI, intelligent workflows, and enterprise-scale integrations.
This is a unique opportunity for a hands-on engineering leader who combines deep technical expertise in Java, Spring Boot, Python, APIs, and AI technologies with the ability to lead distributed engineering teams and deliver large-scale transformation programs. The successful candidate will help define, build, and scale AI-driven solutions that support infrastructure services across multiple channels, including ticketing systems, call centers, and chatbots.
Key Responsibilities
Engineering Strategy & Architecture

• Define and execute the engineering vision and technical roadmap for enterprise infrastructure automation initiatives.
• Lead the adoption of Applied AI and Generative AI technologies to improve operational efficiency and user experience.
• Drive API-first architecture, integration standards, and governance across internal platforms and enterprise applications.
• Evaluate emerging technologies and recommend solutions aligned with business transformation objectives.
• Design scalable, reusable automation frameworks and intelligent service delivery capabilities.

AI & Automation Delivery

• Lead development of conversational AI solutions capable of resolving a significant percentage of internal infrastructure support requests.
• Build and scale automation capabilities supporting infrastructure domains such as access management, applications, network services, and platform operations.
• Drive implementation of AI-powered solutions across multiple engagement channels, including tickets, chat, and voice.
• Establish metrics and KPIs to measure automation effectiveness, adoption, service quality, and business impact.
• Ensure all AI agents and automation solutions align with enterprise governance and platform standards.

Technical Leadership

• Remain actively involved in architecture, design, troubleshooting, and solution development.
• Provide technical direction for engineering teams developing microservices, AI-powered applications, and integration platforms.
• Lead complex enterprise integrations involving multiple systems, platforms, and stakeholders.
• Champion engineering excellence, modern development practices, and continuous improvement.

Team Leadership & Talent Development

• Lead and mentor geographically distributed engineering teams across multiple locations and workstreams.
• Drive workforce planning, resource allocation, and team growth strategies.
• Foster a culture of innovation, accountability, collaboration, and technical excellence.
• Develop engineering talent through coaching, mentorship, and career development.

Program & Stakeholder Management

• Own delivery execution across a multi-year transformation roadmap.
• Establish governance processes including sprint management, release planning, milestone tracking, and risk management.
• Partner with engineering, operations, architecture, and executive leadership to align technology initiatives with business outcomes.
• Communicate progress, risks, and strategic recommendations to senior leadership.

Required Qualifications
Leadership Experience

• 10+ years of progressive software engineering experience.
• 5+ years leading engineering organizations, technical programs, or transformation initiatives.
• Proven experience managing multiple engineering teams across locations and disciplines.
• Demonstrated success delivering large-scale enterprise technology transformation programs.

AI & Automation

• Experience implementing Applied AI, Generative AI, or intelligent automation solutions in enterprise environments.
• Strong understanding of:
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • AI/ML pipelines
  • Conversational AI platforms
  • AI governance and responsible AI practices
• Experience measuring, optimizing, and scaling automation programs.

Application Development

• Deep expertise with:
  • Java
  • Spring Boot
  • Spring Security
  • Spring Cloud
  • Spring Data
  • RESTful APIs
• Strong hands-on development experience and willingness to remain engaged technically.

Integration & Distributed Systems

• Experience building large-scale distributed systems and enterprise integrations.
• Expertise with:
  • API design and governance
  • Event-driven architecture
  • Kafka and/or RabbitMQ
  • OAuth 2.0 and OpenID Connect
  • Kubernetes and Docker
• Proven success integrating complex enterprise applications and platforms.

Agile & Delivery

• Experience leading teams operating in Agile delivery environments.
• Strong understanding of software development lifecycle, release management, and operational excellence.

Preferred Qualifications

• Experience within financial services, banking, or highly regulated enterprises.
• Experience leading enterprise help desk, infrastructure operations, or service automation initiatives.
• Background building omnichannel customer or employee support solutions.
• Experience with enterprise AI platforms and agent-based architectures.
• Advanced degree in Computer Science, Engineering, or related discipline.

Ideal Candidate Profile
The ideal candidate is a hands-on technology leader who can architect solutions, lead engineering teams, and personally dive into complex technical challenges. They will bring experience building enterprise-scale automation platforms, integrating AI into operational workflows, and driving measurable business outcomes through technology transformation. This individual should be equally comfortable discussing API architecture with engineers, reviewing code, presenting strategy to executives, and leading large distributed teams.

All your information will be kept confidential according to EEO guidelines.