About The Position

About the Role Altera is seeking a visionary and hands‑on Director of AI Transformation & Engineering Excellence to lead enterprise‑wide AI initiatives that accelerate productivity, modernize engineering workflows, and drive innovation. In this role, you will architect advanced AI/ML solutions, build and scale Altera’s AI Office, and elevate engineering excellence across the organization. This position is ideal for a deeply technical leader who thrives at the intersection of strategy, execution, and organizational transformation.

Requirements

  • 10+ years of hands‑on AI/ML engineering or applied research leadership.
  • MS or PhD in Machine Learning, AI, Computer Science, or related field.
  • Deep expertise in designing, developing, and deploying large‑scale AI/ML solutions.
  • Strong proficiency in Python, and frameworks such as PyTorch, TensorFlow, and Scikit‑learn.
  • Experience leading technical teams and building AI capabilities from the ground up.
  • Proven track record in driving AI‑enabled productivity improvements or engineering transformations.
  • Excellent communication, cross‑functional leadership, and stakeholder alignment skills.
  • A collaborative mindset, high ownership, and a team‑first, can‑do approach.

Nice To Haves

  • Experience launching or leading an AI Center of Excellence (CoE).
  • Expertise in LLMs, generative AI, RAG systems, and vector retrieval technologies.
  • Familiarity with cloud platforms (Azure, AWS, GCP) and scalable distributed systems.
  • Publications, patents, or research contributions in ML/AI.

Responsibilities

  • Lead the strategic planning, design, and execution of AI‑driven transformation initiatives across Altera.
  • Architect scalable, production‑grade AI/ML systems that improve engineering throughput and business productivity.
  • Build and mentor an AI Office team focused on innovation, enterprise enablement, and continuous improvement.
  • Partner with technology, product, and business leaders to identify and develop AI opportunities with measurable ROI.
  • Champion engineering excellence—coding standards, MLOps best practices, automation, and performance optimization.
  • Stay ahead of advancements in AI, LLMs, generative models, and intelligent automation to guide technology direction.
  • Engage in hands‑on prototyping, model development, and technical reviews.
  • Define KPIs, metrics, and dashboards to track the impact of AI transformation efforts.
  • Foster a culture of collaboration, experimentation, and a strong can‑do attitude.
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