Drimva

Lilt

Senior Technical Program Manager, Applied AI

$143K–$178K

Boston, MA +4 · Hybrid · Manager · Full-time · Posted Oct 19, 2026

Location
Boston, MA
Denver, CO
Seattle, WA
USA
San Francisco, CA
Experience
10+ years of industry experience with a B.S. or M.S.; alternatively, 5+ years in a high-growth AI/Engineering environment with a Ph.D.
Education
B.S. or M.S. in Computer Science, AI, or a related technical field; alternatively, a Ph.D.
Visa sponsorship
Authorization to work in the U.S. is a precondition of employment.

About the job

Leads technical programs and data-delivery operations for frontier AI labs, developing benchmark workflows and ensuring high-quality datasets for LLMs and multimodal models.

What you'll do

  • Propose and co-develop benchmarks with research lab partners, aligning deliverables with research objectives.
  • Manage end-to-end programs delivering large-scale datasets and engineering milestones; oversee pipelines across text, image, video, and audio.
  • Coordinate research, engineering, and production teams to implement automated and human-in-the-loop quality control.

What they ask for

  • B.S. or M.S. in Computer Science, AI, or a related technical field, with 10+ years of industry experience; alternatively, a Ph.D. with 5+ years of experience in a high-growth AI/Engineering environment.
  • Experience founding or scaling a venture, or working in an early-stage startup while driving business growth and strategic initiatives.
  • Proven experience managing data pipelines for LLMs or multimodal models, with understanding of training, inference, and multilingual and multi-domain data diversity.
  • Experience managing high-throughput programs where quality control is mission-critical, including automated validation at scale.

Nice to have

  • Fluency in multiple human languages.
  • Python and modern AI frameworks such as PyTorch or LangChain.

Pay

$142.8K – $178.5K (base salary; currency not specified)

Tools

LLMs, PyTorch, LangChain, Python

AI focus

Leads programs and data workflows that support training LLMs and multimodal models, including benchmark development and data quality control.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)