AI Platform Engineering

AI Platform Engineering

📍 Location: Springfield, MA, United States

🏢 Industry: Financial Services

💼 Work Setting: Hybrid

Are you passionate about building the platforms that power AI innovation, leading high-performing engineering teams, and driving the development of scalable cloud-native AI infrastructure?

Join a forward-thinking technology organization where you'll lead a team responsible for delivering the foundational platforms, tools, and infrastructure that enable enterprise AI development. As an Engineering Manager / Director – AI Platform Engineering, you will combine people leadership, technical strategy, and execution excellence to build scalable AI platforms while fostering a culture of innovation, collaboration, and continuous improvement.

Key Responsibilities

Lead & Develop High-Performing Engineering Teams

• Lead, mentor, and grow a team of platform and infrastructure engineers responsible for AI platform capabilities.
• Oversee hiring, onboarding, performance management, career development, and team engagement initiatives.
• Foster a culture of collaboration, accountability, technical excellence, and continuous learning.
• Remove obstacles and empower teams to perform at their highest level.

Drive AI Platform Strategy & Execution

• Partner with technical leaders, product teams, and stakeholders to execute against the AI platform roadmap.
• Translate strategic objectives into actionable plans, milestones, and delivery schedules.
• Ensure successful execution of platform initiatives while balancing technical priorities, business needs, and operational requirements.
• Manage dependencies, risks, and resource allocation across multiple initiatives.

Provide Technical Leadership

• Contribute to architecture reviews, technical planning sessions, and platform design discussions.
• Guide the development of scalable infrastructure supporting AI applications, machine learning workloads, and intelligent automation solutions.
• Influence decisions related to platform architecture, cloud-native technologies, developer tooling, and operational frameworks.
• Maintain sufficient technical depth to provide direction and support engineering teams effectively.

Champion Engineering Excellence

• Establish and maintain standards for software quality, platform reliability, security, scalability, and operational maturity.
• Promote best practices in system design, code quality, documentation, observability, monitoring, and incident management.
• Ensure teams adopt effective engineering processes that support long-term platform sustainability.
• Drive continuous improvement across development and operational practices.

Manage Stakeholder Relationships

• Communicate project progress, delivery status, risks, and resource needs to leadership and business stakeholders.
• Translate technical concepts and trade-offs into clear business-focused recommendations.
• Foster strong partnerships across engineering, product, AI, cloud, security, and business teams.
• Align stakeholders around strategic priorities and delivery outcomes.

Build Scalable AI & Cloud Platforms

• Support the development of cloud-native platforms that enable AI, machine learning, and advanced analytics capabilities.
• Guide platform initiatives focused on scalability, multi-tenancy, reliability, and developer enablement.
• Ensure infrastructure supports secure, efficient deployment and operation of AI solutions.
• Contribute to platform strategies that improve developer productivity and user experience.

Improve Operational Excellence

• Establish reliable operational processes, service management practices, and support models.
• Drive improvements in system availability, performance, monitoring, and incident response.
• Promote strong documentation standards and knowledge-sharing practices across teams.
• Ensure effective governance and operational readiness for platform services.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical discipline.
• 3 years of experience managing software engineering, platform engineering, infrastructure, or technology teams.
• 5 years of hands-on software engineering, platform engineering, cloud engineering, or related technical experience.
• Proven experience hiring, coaching, mentoring, and retaining engineering talent.
• Strong understanding of cloud-native architectures, distributed systems, and modern infrastructure platforms.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Kubernetes, containerization, networking, and scalable platform architectures.
• Experience leading complex technology initiatives from planning through production deployment.
• Familiarity with AI/ML infrastructure, model deployment, inference systems, or AI platform ecosystems.
• Strong written, verbal, and stakeholder communication skills.

Preferred Qualifications

• Experience building and scaling internal developer platforms or shared engineering services.
• Strong understanding of developer experience principles and platform product management concepts.
• Knowledge of AI governance, responsible AI practices, model evaluation, or AI safety frameworks.
• Ability to influence architectural decisions while maintaining strong people leadership.
• Experience contributing to platform engineering, cloud infrastructure, automation, or machine learning ecosystem initiatives.
• Familiarity with AI application infrastructure, LLM integrations, agent-based systems, or intelligent automation platforms.
• Experience operating within highly dynamic environments and leading teams through ambiguity.
• Advanced degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
• Demonstrated commitment to technical excellence, collaboration, and continuous improvement.

What You'll Gain

• Opportunity to lead the platform initiatives that enable enterprise-wide AI innovation.
• Exposure to cutting-edge technologies spanning AI, machine learning, cloud infrastructure, platform engineering, and automation.
• Significant influence on technical strategy, engineering culture, and platform direction.
• Collaboration with AI engineers, cloud architects, product leaders, and business stakeholders.
• A leadership role focused on shaping the future of scalable AI development and developer productivity.
• Continuous opportunities for professional growth, innovation, and organizational impact.