Delivery Manager (Coding Projects)

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 the delivery of high-quality data and model improvements.

You will serve 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.). A key aspect of this role includes leading our most important code workstream, while also providing support and calibration guidance to other code teams.

Location Requirement: Candidates must be based in the U.S. (West Coast strongly preferred).

Key Responsibilities:

Client Engagement & Operational Oversight

• Act as the strategic point of contact for clients - gathering requirements, aligning on quality expectations, and managing quality 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.
• Work closely with LLM researchers to deeply understand their thinking styles and objectives.
• Translate ambiguous or loosely defined research goals into clear, executable tasks for technical teams.
• Proactively flag risks and drive resolution to ensure uninterrupted, high-quality delivery.

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 and Client Researchers 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.
• Ensure technical soundness, review compliance, and strategic alignment across delivery streams.

Required Qualifications:

• 4-8 years of experience in a Delivery Manager, Program Manager, or similar role within a technical or data-driven environment at a large company
• 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 working closely with LLM researchers and familiarity with how they think, communicate, structure projects, and measure success
• Demonstrated success in translating ambiguous or high-level research directions into actionable plans for engineering and delivery teams.
• Proven ability to translate research ambiguity into clear tactical execution plans
• Strong background leading technical delivery efforts and code-heavy teams
• Effective communicator, both in async and live settings, across technical and non-technical audiences.
• 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:

• US-based (West Coast preferred)
• 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, an exceptional communicator, 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.
• You should also bring a deep understanding of how LLM researchers think and operate—enabling you to convert their often ambiguous instructions into structured, actionable workflows that drive high-quality data delivery.