Jobs at Brain Co.

Build and deploy production machine learning systems, including LLMs, agents, and RAG applications, for healthcare, government, energy, and other regulated industries. Responsibilities include developing scalable data pipelines, optimizing model performance, monitoring deployed models, translating research into practical solutions, collaborating with leaders and cross-functional teams, and contributing to software engineering practices. The role is designed for a 2027 bachelor's graduate with hands-on generative AI and machine learning framework experience.

Build backend services, data pipelines, APIs, distributed systems, developer tools, and shared platform capabilities for AI products. Develop ML experiment tracking, artifact management, and automated training and evaluation pipelines. Improve reliability, latency, and throughput while collaborating with Product and ML teams. Own scoped projects involving implementation, testing, maintenance, and clean API design for enterprise and government customers.

Build and deploy production-grade AI applications across front-end, back-end, and data workflows. Translate customer problems into product requirements, integrate AI models, optimize application performance and reliability, evaluate AI outputs, and iterate using customer feedback. The role supports impactful projects for government, healthcare, and industrial customers, with ownership across the full product lifecycle.

Leads complex government AI deployments from pre-sale discovery through production adoption, overseeing client relationships, delivery planning, cross-functional execution, change management, and executive communication. Translates agency workflows into technical requirements, manages risks and dependencies, drives measurable outcomes, and converts deployment feedback into product improvements. Builds deployment playbooks, operating cadences, and future delivery teams while supporting renewals and expansions. Requires strong AI/ML and enterprise systems fluency, senior stakeholder leadership, and 30–50% travel.

Own the financial services product line from discovery through launch and iteration. Set the roadmap, determine which deployment capabilities become core product features, conduct user discovery, define quality standards, and establish accuracy, human-review, citation, and safe-failure models for regulated workflows. Prototype in design or code, collaborate with engineers and designers, understand the market, and deliver reusable AI capabilities across financial institutions.

Conduct AI diligence for private equity and corporate sponsors, evaluating target companies’ AI strategies, data infrastructure, and technical maturity. Translate technical findings into investment and value-creation recommendations, manage client relationships and engagement workstreams, prepare presentations and deliverables, and collaborate with engineering and product leaders to define feasible AI solutions. The role requires strong analytical, communication, commercial, and AI/ML literacy skills in a fast-paced startup environment.

Own full-cycle technical recruiting for AI/ML, AI Product, and AI Platform engineering teams. Partner with leadership to define hiring needs, design sourcing strategies, manage candidate experience, build market maps and pipelines, negotiate complex offers, and represent Brain Co. at events to attract top technical talent.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

As a Product Designer, you will lead design efforts, collaborate with stakeholders, and establish design systems for AI-driven software products.

Lead end-to-end delivery of enterprise AI engagements: run discovery, size value, define features, coordinate cross-functional teams, drive adoption and change management, and own commercial expansion and program outcomes in regulated environments.

Lead and build core internal and go-to-market operations: procurement, onboarding, vendor management, deal processes, pipeline reporting, and durable systems. Partner cross-functionally with finance, legal, product, and engineering to scale operational infrastructure, automate workflows, and make company goals and metrics legible.

As a Product Manager, you'll own a product area, translate business needs into PRDs, collaborate with teams, and drive product iteration and improvement.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Serve as the first in-house attorney focusing on commercial legal matters, negotiating deals, and providing legal oversight on AI and regulatory projects.

Build core, shared ML capabilities for a production platform: foundation models for documents, extraction agents, model routing, unified evaluation, and continuous improvement pipelines. Own end-to-end capability development, production deployment, and cross-team support to improve accuracy, latency, cost, and reliability across institutional workflows.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.