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Senior AI Engineering Lead
Senior AI Engineering LeadABM Industries • Sugar Land, TX, US
Senior AI Engineering Lead

Senior AI Engineering Lead

ABM Industries • Sugar Land, TX, US
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Overview

Position Title : Senior AI Engineering Lead

Industry Group : Corporate

Reporting Manager Title : VP Technology

Travel Required? No

Direct Reports? No

Responsibilities

  • Frontier AI Research & Model Engineering

Pioneering Research : Lead fundamental and applied research in areas like Generative AI, Multi-modal Foundation Models, and advanced agentic systems.

  • Model Optimization

    • Drive the research and implementation of advanced techniques for Model Alignment (e.g., RLHF, DPO), Quantization, and Distillation to significantly improve the performance, cost, and latency of large-scale models for real-time inference.

  • Data-Centric AI

    • Design and implement innovative strategies for data curation, synthetic data generation, and active learning to continuously enhance model performance with minimal human labeling.

  • AI Safety and Trust

    • Establish methods for AI Guardrails, Adversarial Robustness, and Bias Mitigation to ensure all production systems adhere to the highest ethical and regulatory standards.

  • AI Architecture & Deployment Leadership

    • System Architecture : Define the technical roadmap and architect end-to-end solutions for deploying frontier AI, including Large Language Models (LLMs), RAG systems with Vector Databases, and Multi-Agent Frameworks (e.g., LangChain, CrewAI).

  • MLOps at Scale

    • Architect and govern a next-generation MLOps platform focused on automated model training, continuous delivery (CI / CD), version control, and comprehensive model monitoring for distributed deployments.

  • Compute Optimization

    • Lead the evaluation of specialized AI infrastructure (e.g., NVIDIA GPUs, TPUs) and design the distributed computing strategy for efficiently training and serving multi-billion parameter models.

  • Technical Authority

    • Serve as the final technical authority, conducting deep-dive architectural reviews and providing technical sign-off for all major AI initiatives across the company.

  • Strategic Management & Mentorship

    • Strategic Direction : Partner with senior leadership to define the long-term AI strategy, research, translating complex research breakthroughs into measurable business value.

  • Technical Leadership

    • Lead and mentor a team of Senior AI Engineers, fostering a culture of rigorous scientific inquiry, engineering excellence, and rapid innovation.

  • Cross-Functional Collaboration

    • Act as the technical bridge between Data & AI Engineering, Product Management, and business stakeholders, clearly communicating complex technical concepts to drive alignment.

    Scope

    Scope Factors (Revenue, Assets, Budget, Profit / Loss, Supervisory) – Collaborate with vendors, tech platform SMEs, external teams and internal resources to deliver AI solutions aligned with business strategy.

    Qualifications – Education & Experience

  • Education & Experience : Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field with 2+ years of post-doctoral professional experience and 6+ years of total experience, OR Master's degree in a relevant field with 8+ years of progressively responsible professional experience.
  • Foundation Model Expertise : Deep theoretical and hands-on expertise in the architecture, training, fine-tuning, and deployment of Large Language Models (LLMs) and / or Multi-modal Models.
  • Programming & Systems : Expert-level proficiency in Python, deep learning frameworks (PyTorch, JAX), and high-performance, distributed computing systems (Kubernetes, Ray, MPI).

    • Qualifications – Other Skills, Abilities & Knowledge

  • Experience with Neuro-Symbolic AI, Reinforcement Learning (RL), or Causal Inference applied to real-world systems.
  • A proven track record of leading the development of a production-grade, multi-agent AI system or autonomous decision-making engine.
  • Deep practical knowledge of AI hardware architecture (GPU / TPU) and its impact on large-scale model performance.
  • Experience in an industry with a strong focus on compliance and Responsible AI governance frameworks.
  • A history of work in model efficiency, distributed training, or novel neural network architectures.
  • Foundational knowledge of cyber security and data governance

    • Qualifications – License(s) & Language(s)

    N / A

    Working Environment and Travel Requirements

    Atlanta Metro area. Minimal travel required, not expected to be more than 20%

    Benefits

    ABM offers a comprehensive benefits package. For information about ABM's benefits, visit ABM Team Member Benefits | Staff & Management

    Recruiting Flyer - Staff & Mgmt

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    Engineering Lead • Sugar Land, TX, US