Position Purpose:
As a Manager, AI Platform Engineering, you will lead the development and evolution of our enterprise Generative AI platform, enabling scalable, secure, and high-impact AI capabilities across the organization. This role combines technical delivery leadership with strategic thinking, overseeing a team of engineers to build and operate GenAI platform services, agentic workflows, and multi-model orchestration.
You will partner with product, data, legal, cybersecurity, and business stakeholders to translate AI use case needs into scalable, reusable platform capabilities that drive enterprise-wide adoption and efficiency. You will ensure alignment with security, privacy, and governance standards while enabling successful delivery and commercialization at scale. In addition, you will collaborate with strategic vendors and internal platform teams to accelerate innovation and support a growing portfolio of AI solutions.
This role is critical to scaling AI adoption across the enterprise, balancing rapid innovation with operational excellence and responsible AI practices.
Key Responsibilities:
- 30% Delivery & Execution:
- Collaborates and pairs with product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions
- Documents, reviews and ensures that all quality and change control standards are met
- Writes custom code or scripts to automate infrastructure, monitoring services, and test cases
- Works with vendors and partners for the successful implementation of critical tooling and platforms
- Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
- Contributes to enterprise-wide tools to drive destructive testing, automation, and engineering empowerment
- Evaluates new technologies for adoption across the enterprise
- Participates in and leads review board sessions to drive consistency across the enterprise
- Fills in on product teams for engineers who are out of the office
- 10% Support & Enablement:
- Fields questions from engineers, product teams, or support teams
- Monitors tools and participates in conversations to encourage collaboration across product teams
- Provides application support for software running in production
- Acts as a technical escalation point for the engineers on the team
- 50% People:
- Provides leadership, mentoring, and coaching to Software Engineers
- Attracts, retains, and develops top talent to build a world class Software Engineering Team
- Conducts annual and mid-year reviews by reviewing individual development plans and team feedback
- Fosters collaboration with team members to drive consistency across product teams, and finds opportunities to expose engineers to career interests
- Acts as a proponent of modern software development practices
- Guides team members in strategy, alignment, analysis, and execution tasks within and across product teams
- Participates in and contributes to learning activities around modern software design and development core practices (communities of practice)
- 10% Learning:
- Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations
- Builds relationships with technology leaders at other companies to learn best practices and elegant solutions to common problems
Direct Manager/Direct Reports:
- Typically reports to the Software Engineer Sr. Manager, Technology Director or Sr. Director.
Travel Requirements:
- Typically requires overnight travel 5% to 20% of the time.
Physical Requirements:
- Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.
Working Conditions:
- Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
Minimum Qualifications:
- Must be eighteen years of age or older.
- Must be legally permitted to work in the United States.
- Mastery of an object oriented programming language (preferably Java)
- Must be legally permitted to work in the United States
Preferred Qualifications:
- 8+ years of related work experience in software engineering, with at least 2 years focused on AI/ GenAI projects for large enterprises.
- Experience with modern software delivery practices, including CI/CD pipelines, containerization, and orchestration technologies (e.g., Docker, Kubernetes), with a strong understanding of deploying and operating scalable, production-grade systems.
- Experience designing or building AI agents and agent-based workflows, including orchestration of LLMs, tools, and external systems in production environments.
- Strong understanding of AI, machine learning, and software engineering concepts, demonstrated through recent certifications or project experience
- Proven track record of managing complex technical projects and leading junior eng