Technical Project Manager / Engineering Lead – AI/ML Infrastructure

We are seeking a highly technical and strategic Project Manager / Engineering Lead to own and advance our engagement with a key strategic partner. The ideal candidate will be the central hub for all technical, operational, and strategic activities. You will be responsible for ensuring the technical success of joint projects, managing complex deliverables, leading a cross-functional engineering team, and deepening the customer relationship to secure future business. This role requires a unique blend of deep technical understanding of AI/ML systems, exceptional project management skills, and strong customer-facing abilities.

Key Responsibilities

• Technical Project Leadership & Execution:
• Own the end-to-end planning and execution of complex technical evaluation projects ● Develop and maintain detailed project timelines, ensuring alignment between engineering efforts and customer milestones.
• Lead daily standups and syncs to track progress, identify risks, and unblock the engineering team
• Manage deliverables such as performance benchmarks, technical reports, and software artifacts.
• Customer & Stakeholder Management:
• Serve as the primary technical point of contact for the customer's engineering teams.
• Manage customer expectations, clearly communicating project status, capabilities, and limitations. This includes being candid about software maturity and guiding the customer toward successful outcomes
• Translate customer requirements and feedback into actionable engineering tasks.
• Prepare and deliver technical briefings and reports to customer stakeholders at all levels.
• Cross-Functional Team Coordination:
• Coordinate the work of a large, distributed team of engineers specializing in compilers, performance SDKs, model bring-up, systems, and packaging.
• Clearly assign action items and ensure accountability across different functional groups. ● Facilitate collaboration between internal teams (e.g., Product, Engineering, GTM) to ensure a unified strategy.
• Technical Analysis & Strategy:
• Understand and articulate the technical differentiators of the platform, such as scale-up/scale-out (SUSO) performance, compilation workflows, and comparative analysis against competitors
• Drive technical decisions on project scope, such as selecting which models (e.g., Llama 70B/405B, Qwen, GLM) to focus on and defining the success criteria for deep engagements.
• Analyze project outcomes to inform product roadmap and future sales strategies.

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