Director, AI Engineering Enablement - REMOTE

About Our Team

Lenovo is building a next-generation AI ecosystem across devices and cloud. As Director, AI Engineering Enablement, you will lead the cross-functional engineering programs that take our AI capabilities from early concept to global launch. This is a technical program leadership role inside engineering, not a generic PMO. You will work closely with leaders across Platform, AI Core Intelligence, AI Experience, Cloud Infra, Quality, SRE & Delivery to ensure we can reliably design, build, test, integrate, and ship AI products at scale.

Your work will be organized around three pillars:

Engineering Programs - leading cross-functional AI engineering initiatives from 01 through global rollout.

Engineering Tools - driving the adoption and evolution of tools that help engineers build, debug, and ship more effectively.

Commercial Engineering Enablement - ensuring what we build can be adopted, deployed, and operated by commercial customers.

Key Responsibilities

1. Engineering Programs

• Lead major cross-functional engineering agile programs within AI Engineering (for example: new AI product lines, reliability/performance hardening, cross-device feature programs, technical migrations).

• Work with functional leaders in Platform, Core Intelligence, Experience, Cloud, and SRE & Delivery to define scope, milestones, technical dependencies, and integration points.

• Ensure programs move from prototype to production with clear gates, owners, and timelines, and that teams are set up for success from the beginning.

• Identify and unblock cross-team issues that threaten program delivery, drive decisions, and keep execution on track.

2. Engineering Tools

• Own the roadmap for engineering-facing tools that support developers and feature teams across AI Engineering (for example: engineering dashboards, debugging utilities, test harnesses, experimentation and telemetry views for engineers).

• Work closely with engineering teams to understand their day-to-day friction points and prioritize tools that materially improve productivity and code quality.

• Ensure common tools and practices are adopted across teams so engineers have a consistent and efficient way of building, testing, and integrating features.

• Partner with SRE & Delivery and Platform teams so engineering tools integrate well with our existing observability and infrastructure stack.

3. Commercial Engineering Enablement

• Partner with security, IT, and commercial product stakeholders to ensure AI Engineering solutions can be adopted by business customers (CIO, CSO, IT organizations).

• Translate commercial requirements such as security posture, deployment and configuration models, integration patterns, observability, manageability, identity and audit into concrete engineering programs and workstreams.

• Coordinate engineering readiness for commercial milestones (previews, pilots, general availability launches) and ensure the right technical checks and documentation are in place.

• Serve as a voice of the commercial customer within AI Engineering, making sure early-stage product decisions anticipate commercial adoption and not just consumer scenarios.

Leadership & Collaboration

• Build and lead a small, high-impact team focused on engineering enablement across these three pillars.

• Collaborate closely with AI Engineering leadership (Platform, Core Intelligence, Experience, Cloud, SRE, TPM) to align programs and tools with their roadmaps and priorities.

• Partner with the broader PMO teams to align engineering plans with product and business timelines, while making sure engineering realities and risks are well understood.

• Communicate status, risks, and tradeoffs clearly to senior leadership, and help drive decisions when plans need to change.

Basic Qualifications

• 15+ years in software or AI engineering, with 10+ years in technical program leadership, engineering management, or equivalent roles.

• Experience leading complex, multi-team engineering programs from 01 and through scale (early-stage to growth-stage, or local to global).

• Experience working with or around AI, platform, or distributed systems (you don't need to be an ML researcher, but you must be comfortable in deeply technical conversations).

• Experience working across highly technical domains (infrastructure, AI systems, client engineering, SRE) and reason about dependencies and risks.

• 25% - 50% travel, includes both domestic and global travel

• Experience improving how engineering teams build and ship: developer workflows, integration practices, test strategies, or tooling adoption.

• Familiarity with commercial / B2B or enterprise requirements (security, IT integration, deployment, manageability) is a strong plus.

• Excellent communication and stakeholder management skills; able to influence without direct authority and to align multiple teams around shared goals.

The base salary budgeted range for this position is $220K - $320K. Individuals may also be considered for bonus and/or commission.

Lenovo's various benefits can be found on www.lenovobenefits.com.

In compliance with Colorado's EPEWA, the expected application deadline for this position is January 5, 2026. This applies to both external and internal candidates.