Jobs at Brain Co.

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.

Lead end-to-end product design for complex AI-driven enterprise and government software. Responsibilities include UX research, interaction and visual design, prototyping, testing, design-system development, and user advocacy. Collaborate with product managers, engineers, and stakeholders to create scalable, accessible, workflow-oriented experiences and experiment with emerging AI design tools.

Owns end-to-end technical recruiting for AI/ML, AI Product, and AI Platform engineering teams. Responsibilities include defining hiring needs, developing sourcing strategies and market maps, managing candidate experience, negotiating complex offers, and representing the company at events and online communities. The recruiter will partner with engineering leadership and executives to attract and close exceptional technical talent across global markets.

Build and grow the insurance business by creating demand, sourcing and qualifying enterprise opportunities, developing quantified value cases, and leading complex multimillion-dollar technology sales through close. The role coordinates product, engineering, deployment, legal, security, and procurement stakeholders; informs product strategy through customer insights; and develops repeatable sales processes. Candidates need deep insurance domain expertise, enterprise sales experience, technical AI fluency, and a record of independently closing complex engagements.

Own Brain Co.'s sales operations systems, CRM data, forecasting, pipeline reviews, pricing approvals, deal handoffs, dashboards, sales planning, and compensation administration. Partner with sales leadership, finance, and general managers to connect bookings with financial plans, improve sales processes, and support enterprise growth. The role requires Salesforce or HubSpot administration, analytical modeling, deal desk experience, and strong cross-functional communication.

Support the design, development, testing, and deployment of AI-powered applications across front-end, back-end, and data workflows. Collaborate with engineers, researchers, product managers, and operators to translate customer needs into product requirements, integrate AI models, evaluate outputs, improve reliability and usability, and ship production-grade tools for government, healthcare, and industrial customers.

AI/ML engineering intern will help design, build, evaluate, and deploy LLM-powered applications and machine learning systems. Responsibilities include developing data pipelines, working with structured and unstructured data, supporting model training and optimization, preparing systems for production monitoring, and collaborating with engineers, researchers, and product teams. The role offers mentorship and hands-on experience applying AI to healthcare, government, and energy workflows.

Interns build backend services, APIs, distributed systems, platform components, developer tools, and AI/ML infrastructure. Responsibilities span design, implementation, testing, deployment, maintenance, reliability, performance optimization, observability, and collaboration with Product, ML, Infrastructure, and customer-facing teams. The role is intended for undergraduate juniors and seniors graduating by June 2028 and offers mentorship through production-focused engineering work.

Build Brain Co.'s financial-services sales business by creating demand, sourcing and qualifying opportunities, developing value cases, leading complex technology engagements through multimillion-dollar close, and coordinating security, legal, procurement, and delivery handoffs. The role also informs product strategy, develops repeatable sales practices, and manages enterprise relationships across banking, lending, wealth management, and real estate investing.

Own new business and account growth across a portfolio of U.S. states. Build executive relationships, identify agency needs, develop value cases, secure funding, lead complex technology deals through close, and expand customer engagements. The role requires navigating state procurement, budgets, contracts, security approvals, and delivery alignment while building a repeatable public-sector sales motion for AI solutions.

Own the company’s operating cadence, including leadership meetings, business reviews, planning, and goal tracking. Prepare board and investor materials, analyze business performance, and lead strategic projects for the CEO and CFO. Design scalable internal processes, support market and partnership evaluations, and drive cross-functional initiatives to completion. The role requires strong analytical, communication, ownership, discretion, and ambiguity-management skills.

Own end-to-end delivery of applied AI deployments for financial-services clients, from discovery through production and sustained adoption. Lead cross-functional teams, manage priorities and risks, define product requirements, drive organizational change, measure customer value, maintain senior client relationships, and identify account expansion opportunities. Build prototypes, evaluate AI outputs, advise on technical trade-offs, and help develop reusable deployment practices.

Manage IT and workplace operations for the San Francisco office, including AV systems, corporate networks, equipment, vendors, and employee support. Provide hands-on hardware and software troubleshooting, administer Okta access, and manage onboarding and offboarding. Lead office installs, equipment purchasing, and conference-room setup while partnering with infrastructure and security teams. Support compliance activities, new-office launches, and potential growth of an IT support team.

Own Brain Co.’s developer platform, including development environments, monorepo tooling, build systems, CI/CD, code-review automation, and engineering workflows. Measure and reduce developer friction through instrumentation and user feedback. Improve reliability, onboarding, adoption, and delivery speed across cloud, regulated, and air-gapped environments. Integrate AI-assisted development tools, support migrations, and operate the platform through its full lifecycle.

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.

Build and deploy production-grade AI systems for regulated institutions. Own ambiguous ML problems end-to-end, including data definition, model training, evaluation, deployment, and monitoring. Work with LLMs, vision models, reinforcement learning, agentic systems, and rule engines to process complex documents and support institutional decisions. Collaborate directly with customers, engineer for accuracy, latency, cost, and reliability, and develop rigorous evaluations and failure-mode taxonomies.

Build shared machine learning capabilities for AI-native platform products, including document extraction, foundation models, model routing, evaluation, agentic systems, and continuous improvement. Translate urgent product-team needs into reusable platform abstractions, own capabilities through production, optimize accuracy, latency, cost, and reliability, and develop feedback and retraining loops that improve deployed systems across regulated institutional workflows.

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.