- Engagement Type Short Term Contract (3 month)
- Start Date Immediate
- 1st Step: AI Interview
- 2nd Step :Delivery Interview
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.- Availability Commitments Required: At least 8 hours per day and minimum 40 hours per week with overlap of 4 hours with PST.
- Note A LinkedIn profile profile is mandatory for review. Please ensure the resume has the link.
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.
