TECHNICAL TRAINING MANAGER

Strategy and customer-facing solutions

Define and drive the end-to-end technology learning strategy (AI, cloud, data, modern engineering, architecture, platforms) aligned to business, delivery, and client needs.
Design and package full-stack talent transformation solutions for strategic clients, including proposals, solution decks, roadmaps, and program architectures.

Lead and coach trainers, architects, and SMEs across AI and other key technology areas to deliver high-quality, hands-on programs.
Introduce new ways of working in tech trainings: labs, projects, hackathons, sandboxes, playbooks, and reusable templates across multiple tech stacks.
Use learning platforms, virtual labs, and analytics to scale and personalize learningacross AI, cloud, data, and engineering.

15 - 17 years across software engineering/architecture/cloud/data/AI, with 5+ years in technical training, presales, or L&D leadership.
Proven experience running large-scale, multi-technology learning programs and presenting confidently to senior client stakeholders.
Strong grounding in modern engineering, cloud platforms, data/analytics, and applied AI, with excellent communication, storytelling, and slide-building skills.

Own competency paths for different personas across AI, cloud, data, engineering, and platforms (developers, architects, SRE/DevOps, PMs, domain experts, leaders).
Guide design of learning on generative AI/LLMs plus adjacent areas such as cloud-native architectures, data engineering, APIs/microservices, security, and observability.
Convert internal and client technology use cases into learning content, labs, and capstones that can be showcased in customer conversations.

Act as technology counterpart to Program Management and L&D Operations for large internal and client-facing programs.
Define entry/exit criteria, assessments, and readiness scorecards for multi-technology academies and transformation initiatives.
Ensure trainers, labs, content, and environments are ready and aligned with program timelines, SOWs, and client commitments.

Certifications across one or more areas (e.g., major cloud providers, data/analytics, architecture, AI/ML, or DevOps) are highly desirable