Strategic Project Lead - Code

Turing

Bengaluru

On-site

INR 3,500,000 - 6,000,000

Full time

14 days+
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Benefits offered by this job

Amazing work culture
Awesome colleagues
Competitive compensation

Job summary

Turing is seeking an operations leader to own the production system behind our AI data programs, turning complex research requirements into predictable, scalable delivery. You will manage data pipelines, quality signals, and large teams of contributors while coordinating with frontier AI labs.

You will inspect code, understand tests, and challenge rubrics to ensure high‑quality output. This role emphasizes hands‑on process optimization and cross‑functional leadership in a fast‑growing

Qualifications

  • Background in software engineering, technical program management or similar high‑velocity environments.
  • Strong analytical and communication abilities to spot bottlenecks and report clearly.
  • Experience working with high‑profile clients and managing expectations.

Responsibilities

  • Own end‑to‑end delivery on projects; design data pipelines from specs to delivery.
  • Ensure data integrity across annotation, evaluation, and curation lifecycles.
  • Coordinate large distributed contributor networks and manage training, performance, and incentives.
  • Act as primary contact for researchers and program managers; translate research intent into task specs.
  • Build playbooks and reusable assets to scale future SPLs and improve operating systems.

Skills

Software eng
Technical PM
Consulting
Startups
Operational envs

Job description

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 looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage. Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com

The Role

You will own the production system behind Turing’s software-engineering data programs, turning complex research requirements into predictable delivery across quality, throughput, contributor performance, timelines, and cost. These programs may involve supervised coding demonstrations, repository-level tasks, agentic trajectories, reinforcement-learning environments, benchmarks, code review, and rubric-based evaluations. They can require coordinating hundreds of distributed software engineers while responding quickly to changing research requirements. This is an operations leadership role with a meaningful technical bar. You must be able to inspect code, understand tests, interrogate quality signals, and challenge a workflow or rubric when it is not producing the intended result. You will not be expected to act as the principal engineer for every program. Your primary responsibility is to build and operate the system that consistently produces high-quality technical work at scale.

What You’ll Own
  1. Operational execution — own end-to-end delivery on every project you run. Design and manage data pipelines from customer specification to final delivery, with full accountability for scope, timeline, and quality. Scope and stand up coding workstreams across supervised demonstrations, agentic trajectories, RL environments, benchmark construction, and rubric-graded evaluation. Diagnose bottlenecks in real time — re-sequence workflows, refine instructions, create incentive systems, and scale review processes to hit throughput targets.
  2. Quality ownership — ensure world-class data integrity on every project. Own quality control across the annotation lifecycle: set the bar, measure against it, and close the gap when it slips. Analyze datasets to identify trends, anomalies, and systematic errors — then fix the root cause, not just the symptom. Implement and continuously improve annotation, evaluation, and curation best practices.
  3. Large-scale coordination — orchestrate the work of 100–1,000+ contributors. Define the required contributor profile and partner with talent teams to source, assess, onboard, and ramp distributed software engineers. Own contributor training, performance management, reviewer capacity, incentives, and corrective actions. Build team-lead and reviewer structures that maintain execution standards across programs involving hundreds of contributors.
  4. Customer relationships — be the face of Turing to the world’s leading AI labs. Act as the primary point of contact for researchers and program managers at frontier AI labs providing clear reporting on progress, quality, risks and recovery actions. Translate research intent into a task specification, and push back when a spec will not produce the signal the researcher actually wants. Build the kind of long-term trust that converts a one-off project into a multi-year partnership — and identify expansion opportunities along the way.
  5. Playbook building — codify what works so future SPLs scale faster than you did. Use Python, SQL or other appropriate tools to automate quality sampling, defect classification, throughput analysis, and weekly reporting. Turn successful workflows into reusable playbooks, quality controls, evaluation assets, and contributor-management systems. Share lessons and mentor other SPLs so each program improves the operating system for the next one.
What We’re Looking For
  • Background in software engineering, technical program management, consulting, finance, startups, or other operationally intense environments, with a proven track record of managing complex, multi‑stakeholder projects.
  • Strong analytical and communication abilities: you can spot a bottleneck in a noisy production environment, build a measurement plan, and communicate the fix to a demanding client in plain language.
  • Customer-facing experience: comfortable working directly with high‑profile clients, managing expectations, and building long‑term relationships.
  • Excited by gritty process optimization and large‑scale execution — you thrive on making complex operations faster, cleaner, and more reliable.
  • You can read and review code. You can follow a pull request in Python, TypeScript, Java, or Go, read a test suite, and judge a delivered task independently.
  • Bonus: Experience with agentic evaluation harnesses, software engineering benchmarks, or RL environments; Experience managing large distributed contributor networks or marketplaces; Prior work at an AI data vendor or a frontier lab
What Success Looks Like
  • 30 days: Complete technical and operational calibration, establish the program baseline, validate acceptance criteria and delivery controls, and independently lead a defined workstream.
  • 90 days: Deliver predictable throughput and quality, improve at least one material operating metric, maintain a trusted risk and reporting cadence, and demonstrate that defects are being detected internally before customer delivery.
  • 180 days: Run concurrent programs with stable quality and cost performance, convert successful workflows into reusable assets, contribute evidence that supports account expansion, and help another lead or team adopt the operating system you built.
Why Turing

Work directly with the world’s leading AI labs at the cutting edge of post-training, evaluation, and agentic AI research.

Real impact on the path to AGI: the data you deliver will directly influence how frontier models are trained and evaluated.

High ownership and influence. You will shape how Turing delivers at scale, with direct visibility to senior leadership.

Direct‑to‑research customers. You will spend your time partnering with the people building the future of AI, not coordinating with procurement.

Advantages of joining Turing
  • Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
  • Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
  • Competitive compensation
  • Don’t meet every single requirement? ... encourage you to apply anyways. You may be just the right candidate for this or other roles.

Turing is proud to be an equal opportunity employer.

We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics.

At Turing we are dedicated to building a diverse, inclusive and authentic workplaceand celebrate authenticity

For applicants from the European Union, please review Turing's GDPR notice here.

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