Customer Success Manager

Responsibilities

• Work with customers to identify high-impact problems and define AI-driven product features to address them.
• Convert customer requirements into clear technical specifications and use cases for internal teams.
• Oversee agile sprints and project timelines, ensuring timely and high-quality solution delivery.
• Travel regionally to engage with users, onboard stakeholders, and gather direct product feedback for continuous improvement.
• Serve as the bridge between customers and internal teams including data scientists, engineers, and product leads.
• Build trusted relationships and ensure the long-term success of deployed solutions.

Requirements

• 3-5 years in customer success, product management, delivery consulting, or technical account management.
• Experience at top-tier product or consulting organizations (e.g., Palantir, Google, Amazon, BCG, McKinsey, etc.)
• Strong understanding of AI/ML concepts, data workflows, and model deployment processes.
• Ability to discuss and assess technical trade-offs with engineering teams.
• Proven ability to build rapport and trust with enterprise customers and senior stakeholders.
• Excellent written and verbal communication, including the ability to simplify technical details for non-technical audiences.
• Hands-on mindset with a bias for action and a strong sense of ownership.
• Experience managing agile product or project delivery cycles.
• Willingness to travel within the region to meet customers and oversee deployments on-site.

Benefits

• Work on transformative AI projects with high-impact clients.
• Join a collaborative, mission-driven team at the forefront of applied machine learning.
• Operate in a fast-paced, agile environment with real-world outcomes.

About the Company

Brain Co. is at the leading edge of productionizing artificial intelligence for real world problems, propelling advancements and shaping the future with pioneering work. Our mission is to ensure that the transformative powers and automation of AI are applied to real world problems in various governments where manual work is still dominant.