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Principal Software Engineer; AI​/ML Architect-Engineer

Job in Lowell, Middlesex County, Massachusetts, 01856, USA
Listing for: UKG
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: Principal Software Engineer (AI/ML Architect-Engineer)

At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform, helping people get paid, grow in their careers, and shape the future of their industries.

We never stop learning, challenging the norm, pushing for better, and celebrating wins along the way. Here you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you.

About the Role

We are searching for an exceptionally skilled and visionary Principal Software Engineer with deep expertise in building, deploying, and scaling generative AI applications. As a key individual contributor at the Principal level, you will drive the architecture, strategy, and development of groundbreaking AI technologies that support our long‑term mission. You will lead the technical vision, strategy, and architectural direction for our GenAI initiatives and help guide the company to stay at the forefront of AI innovation.

Responsibilities
  • Architectural Vision & Strategy:
    Define and drive the generative AI architecture strategy, ensuring UKG remains at the leading edge of AI innovation, and communicate a cohesive architectural vision that aligns with business goals.
  • Technical Leadership:
    Serve as the primary technical visionary for generative AI, guiding advanced methods such as transformer models, diffusion models, and GANs, and setting technical standards for scalability, security, and efficiency.
  • Cross‑Functional

    Collaboration:

    Work closely with executive leadership, product management, data science, and engineering teams to establish and prioritize GenAI initiatives and align on requirements and objectives.
  • Innovation & Research:
    Conduct hands‑on research in generative AI, stay current with emerging technologies, and lead the exploration and implementation of state‑of‑the‑art GenAI techniques.
  • Mentorship & Culture Building:
    Mentor senior engineering leaders, foster a culture of AI excellence and continuous innovation, and champion best practices in AI/ML development and MLOps.
  • Community Engagement:
    Represent UKG in the AI community through publications, speaking engagements, and industry forums.
  • Scalable Solutions:
    Oversee deployment of large‑scale AI models, optimizing performance, cost, and resource efficiency, and establish guidelines for production‑ready AI/ML systems.
  • Governance & Standards:
    Define and enforce development methodologies, CI/CD standards, and architectural guidelines for AI solutions, and maintain documentation of technical roadmaps.
Qualifications
  • Educational background: MS or PhD in Computer Science, AI, Machine Learning, or related field, or equivalent industry experience.
  • Experience:

    12+ years in software development and AI, with at least 5 years of hands‑on experience in generative AI, NLP, or related fields, and proven expertise in architecting and deploying large‑scale AI/ML systems.
  • Technical proficiency:
    Expert‑level skills in programming languages such as Python and Java, AI frameworks such as Tensor Flow or PyTorch, and cloud platforms including AWS, Google Cloud, or Azure; strong MLOps practices for large‑scale model training and deployment.
  • AI methodologies:
    In‑depth knowledge of generative AI techniques—including transformer models, diffusion models, GANs, large language models, and multi‑modal architectures—and familiarity with NLP and machine learning algorithms.
  • Industry influence:
    Recognized thought leader in AI, with a record of publications in top‑tier conferences or journals and a strong network within the AI research community.
  • Problem‑solving & strategy:
    Exceptional problem‑solving skills and a proven ability to influence and implement long‑term AI‑driven strategic initiatives.
Preferred Qualifications
  • Compliance & Responsible AI:
    Experience in high‑compliance environments, privacy‑preserving AI techniques, and responsible AI practices.
  • Optimization expertise:
    Proven record of optimizing AI models for cost‑efficiency at scale, through compression, distillation, and efficient…
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