Software Engineering Manager (delivery)

About Turing

Based in Palo Alto, California, Turing is one of the world's fastest-growing AGI infrastructure companies accelerating the advancement and deployment of powerful AI systems. Turing has two main business lines: Turing AGI Advancement, which works with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, STEM and frontier knowledge; and Turing Intelligence, which leverages learnings from advancing frontier AGI to build real-world AI systems that solve mission-critical priorities for Fortune 500 Companies. Powering this growth is Turing’s AI-powered vetting and matching engine and its fine-tuning platform, ALAN, which accelerates workflows for model evaluations, fine-tuning, reinforcement learning, and agent development.

Turing has received numerous awards, including Forbes's "One of America's Best Startup Employers," #1 on The Information's annual list of "Most Promising B2B Companies," and Fast Company's annual list of the "World's Most Innovative Companies." Turing's leadership team includes AI technologists from industry giants Meta, Google, Microsoft, Apple, Amazon, Twitter, McKinsey, Bain, Stanford, Caltech, and MIT. For more information on Turing, visit www.turing.com. For information on upcoming Turing AGI Icons events, visit go.turing.com/agi-icons.

Position Overview:

As a Delivery Manager, you will lead the end-to-end execution of LLM training projects involving Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and Reinforcement Learning from Execution Feedback (RLEF). You will manage a cross-functional team of AI Trainers, Leads and Engineering Managers to ensure delivery of high-quality data and model improvements.

You will operate as the senior-most project owner, accountable for strategic client alignment, throughput, quality, and operational efficiency across multiple streams and programming languages (Python, JavaScript, Java, etc.).

This role requires hands-on delivery leadership, team scaling, stakeholder management, and a clear understanding of both technical and operational dimensions of LLM development.

Key Responsibilities:

1. Project Leadership & Cross-Functional Management

• Own full project lifecycle from kickoff and scoping to delivery and stabilization.
• Manage multiple concurrent LLM training streams (Evals, SFT, RLHF, RLEF, etc.,) across languages and domains.
• Lead and coordinate distributed remote teams including AI trainers, team leads and engineering managers.
• Maintain strong alignment with Engineering Managers, ensuring delivery of technically sound and review-compliant datasets.
• Monitor throughput, quality, rework, review coverage and staffing requirements.

2. Client Engagement & Operational Oversight

• Act as the strategic point of contact for clients - gathering requirements, aligning on expectations, and managing feedback loops.
• Build and maintain detailed project trackers, dashboards, and delivery health reports.
• Proactively flag risks and drive resolution to ensure uninterrupted, high-quality delivery.
• Set up scalable processes, SOPs, and review systems to mature project operations.

3. Quality Governance & Continuous Improvement

• Own delivery-level quality KPIs across all roles from trainers to engineers.
• Ensure clarity, accuracy, and completeness in outputs: code, responses, explanations, and evaluations.
• Work closely with team leads to implement quality review loops and resolve systemic quality gaps.
• Identify inefficiencies and continuously optimize workflows and operational structure.
• Ensure all output meets the highest standards expected by AI researchers and clients.

Required Qualifications:

• 4–8 years of experience in a Delivery Manager, Program Manager, or similar role within a technical or data-driven environment.
• Proven track record in managing end-to-end project lifecycles, scaling teams, and optimizing delivery pipelines.
• Strong experience in client-facing roles involving requirements gathering, delivery tracking, and stakeholder alignment.
• Experience managing diverse and distributed teams.
• Skilled in driving team performance, managing escalation workflows, and balancing speed, quality and cost.
• Working knowledge of Python and/or JavaScript to effectively engage with Engineering Managers and assess code-level output quality.
• Proficient in using project management and tracking tools (e.g., Airtable, Notion, JIRA, Asana, Google Sheets).
• Exceptional communication and documentation skills - comfortable leading async and live updates across technical and non-technical audiences.
• Strong decision-making, prioritization, and conflict-resolution abilities in dynamic, high-stakes environments.

Preferred/Bonus Qualifications:

• Background in Machine Learning or Data Science is a plus.
• Familiarity with LLM concepts, training cycles, or evaluation methods (e.g., RLHF, SFT, RAG).
• Hands-on experience with LLM APIs (GPT, Gemini, Claude, etc.) and RAG workflows.

Ideal Candidate Profile:

• Brings a blend of technical fluency and operational leadership, enabling you to lead delivery in AI/LLM training projects without needing to code.
• Take initiative to unblock teams, address quality issues, and streamline workflows.
• A systems thinker, able to design processes and tracking mechanisms that scale with team growth and delivery complexity.
• Are client-obsessed, with strong stakeholder instincts and the ability to proactively manage expectations, risks, and feedback loops.
• Have a continuous improvement mindset, always looking for ways to evolve team structure, workflows, tooling, and delivery KPIs.
• An empathetic leader, able to manage global teams in async environments while building trust and accountability.