Strategic Project Lead - Code

Turing; Bengaluru; Hybrid; INR 2,500,000 - 4,200,000; Full time

Benefits offered by this job

Collaborative work environment

Competitive compensation

5 days a week

Job summary

Turing, based in San Francisco, leads frontier AI data programs and operates scalable systems for research. You will own the production system behind our software-engineering data programs, turning complex requirements into predictable delivery across quality, throughput, and cost.

This is an operations leadership role requiring coordination of hundreds of distributed engineers, deep process optimization, and strong communication with frontier AI labs.

Qualifications

• Background in software engineering or TPM with complex multi-stakeholder projects.
• Strong analytical and communication abilities.
• Customer-facing experience with high-profile clients.
• Excited by process optimization and large-scale execution.
• Ability to read and review code in multiple languages.

Responsibilities

• Own end-to-end delivery on every project.
• Design and manage data pipelines with quality and timelines.
• Coordinate 100–1,000+ contributors across programs.
• Maintain world-class data integrity across the annotation lifecycle.
• Engage researchers and program managers, reporting progress and risks.

Skills

Software engineering background

Analytical abilities

Strong communication

Customer-facing experience

Code reading/reviewing

Tools

Python

TypeScript

Java

Go

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.

Values

• We are client first : We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
• We work at Start‑Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
• We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.

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? 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, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

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