Strategic Project Lead – Software Engineering

About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

Role Overview

As a Senior Program Lead, you will own the production systems behind Turing’s software-engineering data programs. You will turn complex research requirements into predictable delivery across quality, throughput, contributor performance, timelines, and cost.

These programs may include supervised coding demonstrations, repository-level tasks, agentic trajectories, reinforcement-learning environments, benchmarks, code review, and rubric-based evaluations. You may coordinate hundreds of distributed software engineers while adapting quickly to evolving research requirements.

This is an operations leadership role with a strong technical bar. You should be comfortable inspecting code, understanding tests, analyzing quality signals, and challenging workflows or rubrics when they do not produce the intended outcomes. Your primary responsibility will be to build and operate a reliable system that consistently produces high-quality technical work at scale.

What Does Day-to-Day Look Like?

• Own end-to-end delivery across scope, timelines, quality, throughput, contributor performance, and cost.

• Design and manage workflows for coding datasets, agentic trajectories, RL environments, benchmarks, and rubric-based evaluations.

• Identify operational bottlenecks and improve workflows through better instructions, sequencing, incentives, review systems, and capacity planning.

• Define contributor requirements and partner with talent teams to source, assess, onboard, train, and ramp distributed software engineers.

• Build team-lead and reviewer structures for programs involving 100–1,000+ contributors.

• Own quality-control systems, analyze datasets for trends and systematic errors, and address root causes.

• Act as the primary customer contact for AI labs, communicating progress, risks, quality trends, and recovery plans.

• Translate research objectives into practical task specifications and push back when requirements may not produce the intended signal.

• Use Python, SQL, or similar tools to automate quality sampling, defect analysis, throughput reporting, and operational reviews.

• Convert successful workflows into reusable playbooks, quality controls, evaluation assets, and contributor-management systems.

• Share operational learnings and mentor other program leads.

Requirements

• Proven experience leading complex, multi-stakeholder programs in software engineering, technical program management, consulting, finance, startups, operations, or a similar environment.

• Strong analytical and problem-solving skills, with the ability to identify bottlenecks, define meaningful metrics, and improve production performance.

• Experience managing distributed teams, contributor networks, marketplaces, or large-scale technical operations.

• Strong customer-facing communication skills, including the ability to manage expectations, communicate risks, and build long-term client relationships.

• Ability to read and review code, understand test suites, and independently assess technical work in languages such as Python, TypeScript, Java, or Go.