Global Brain Corporation

Application Engineer

• Own secure development practices across our products: AuthN/AuthZ patterns, secrets management, input handling, and secure-by-default standards that engineers can follow without security becoming a bottleneck.
• Integrate security into the development lifecycle — code review, CI/CD pipelines, and pre-deployment checks — catching risk before it reaches production.
• Conduct threat modeling across product features and release cycles, translating risk into concrete controls that ship alongside each product.
• Build and maintain security tooling and automated checks that scale your reach across the codebase — using AI to move faster and cover more ground than manual review alone could.
• Own the application-layer security model for Brain Co.'s agentic products — how agents are scoped, what they are authorized to do on behalf of users, and where trust boundaries sit between the agent and the external systems it touches.
• Define secure patterns for how agents integrate with third-party systems and APIs: how credentials are stored and scoped, how responses are validated before being acted on, and how each product limits what agents can do with what they get back.
• Work directly with product and ML engineers during feature development to define secure agent design patterns: tool scoping, permission boundaries, output validation, and safe handling of user context across multi-step workflows.
• Build reusable secure-by-default patterns for agent development — design guidelines, review checklists, and code-level guardrails — so that security standards scale as new agent capabilities are built.
• Produce security artifacts for agent features and product deployments: threat models, architecture reviews, and documentation that supports delivery into regulated customer environments.
• Define and enforce data protection standards at the application layer — ensuring sensitive customer data (PHI, PII, government records) is handled correctly as it flows through AI pipelines and surfaces in agent outputs.
• Build safeguards against unauthorized data exposure across our products: access controls, output filtering, and audit logging that make data handling attributable and reviewable.
• Design secure data handling patterns for AI features operating on regulated data, working with platform and ML teams to ensure the application layer upholds its share of the data protection contract.

AI Application Security Engineer

Account Manager

• Own the full lifecycle of government opportunities: intro → qualification → stakeholder navigation → close → early relationship ownership
• Own a revenue target tied to closing Signed Design Partnerships (SDPs) and converting them into paid deployments
• Build, manage, and advance a pipeline of public sector opportunities from early signal through close
• Convert warm inbound / network-driven opportunities into Signed Design Partnerships (SDPs)
• Navigate complex government buying processes across agencies, departments, and stakeholders
• Drive momentum in ambiguous environments where there is interest but no clear owner
• Build relationships across city/state agencies, mayoral offices, permitting/ infrastructure departments, and public sector ecosystems
• Partner closely with product & engineering to translate customer needs into deployable solutions
• Operate as a hybrid, seller (close deals), operator (move things forward without structure), and early account owner (maintain momentum post-close

Sales and Partnerships, Public Sector

Security Engineer

• Own the corporate technology layer end-to-end — identity and access management, SaaS tooling, device security, and the employee-facing systems that keep a fast-growing company running safely.
• Own our Okta environment and consolidate SSO: migrations, managing provisioning, lifecycle automation, and federation across all departments.
• Implement and improve our 3-tier access entitlement model: auto-grant for Tier 1, manager approval for Tier 2, manager + security approval for Tier 3.
• Build and operationalize HRIS-triggered provisioning and offboarding automation across our identity and SaaS stack.
• Support access review programs and contribute to SOC 2 compliance efforts — maintaining audit trails, approval chains, and provisioning logs.
• Contribute to Zero Trust and endpoint security initiatives: device trust, EDR integration, MDM, and least-privilege access across corporate and BYOD devices.
• Drive SaaS hygiene across our tooling estate — shadow IT discovery, configuration hardening, and data classification in partnership with the security team.
• Build the integrations and automation that eliminate manual IT work — connecting identity, HRIS, and SaaS tooling into scalable provisioning workflows.
• Own the access request process end-to-end, and maintain the runbooks, documentation, and self-service resources that keep the team unblocked.
• Partner on IT support for a 70+ person team –– triaging and resolving hardware and software issues with pragmatism and good judgment.
• Own device lifecycle and support new hire onboarding end-to-end, ensuring a seamless Day 1 experience.

IT Security Engineer

Technical Recruiter

• Partner directly with engineering leadership to identify, engage, and inspire world-class engineers to join our team.
• Own pipeline creation for competitive talent pools in AI/ML, Product, and Platform.
• Map talent markets, create targeted outreach strategies, and build engaging candidate experiences.
• Scale Brain Co.’s engineering team to meet demand from Fortune 50 companies and government systems.

Technical Sourcer, Engineering

Recruitment

• Interview Coordination: Schedule candidate interviews across time zones, manage logistics, and ensure all parties are prepped and aligned
• Candidate Experience: Be the main point of contact for candidates throughout the process. Answer questions, provide updates, and make the experience smooth and welcoming
• ATS/ System Maintenance: Keep our ATS (Ashby) updated and clean. Manage candidate records, interview plans, and internal notes
• Operational and Sourcing Support: Help streamline recruiting processes, support sourcing projects, and jump in on ad hoc recruiting tasks as needed

Recruiting Coordinator

Attorney

• Own the deal review cycle across our active pipeline — coordinating redlines with external counsel, aligning stakeholders, and bringing leadership a single, clear recommendation on each deal
• Build the playbooks, templates, and systems that let us review 2–3x more deals per week without adding headcount
• Develop Brain Co's point of view on key commercial terms — especially around AI-specific IP, data rights, indemnification, and pricing
• Surface patterns and flag risks so leadership can make faster, more informed decisions on deal structure
• Manage relationships with our external legal partners to ensure quality, consistency, and cost efficiency

Legal Ops, Contract, Part Time

Product Manager

• Drive product execution and vision within Brain Co.'s Government and Commercial AI initiatives
• Own a product initiative end-to-end — from discovery and scoping through design, development, and delivery
• Incubating new product and business opportunities that underpin our mission and goal
• Write crisp PRDs and translate problems into actionable technical requirements
• Conduct regular discovery conversations with customers, and surface insights and inform the roadmap
• Groom the product backlog and drive prioritization in partnership with engineering, design, and data science
• Measure impact, gather feedback, and iterate continuously

Product Manager – GovAI

Architect

• Walk us through how you submit
• Use the product on a project
• Review AI output on real permit submissions and flag errors
• Help us understand how review works across jurisdictions
• Review sample packages and provide feedback

Builder – Architect – Engineer Expert Consultant, Part-Time Contractor

Platform Engineer

• Build the security foundations of our AI platform: identity, isolation, and access control.
• Embed security into cloud infrastructure, Kubernetes, and deployment workflows.
• Create paved roads and guardrails so engineers can move fast safely.
• Own auditability, detection, and incident readiness.

AI Platform Engineer, Security

Technical Program Manager

• Own labeling operations end-to-end across multiple AI/ML projects
• Source, interview, onboard, and manage labelers, agencies, and subject matter experts
• Write, refine, and maintain clear labeling instructions, examples, and task definitions
• Partner with engineers to determine the right labeling approach, including inputs, outputs, workflows, and quality requirements
• Identify and organize the right data and example sets for labeling
• Keep labeling work on track against project milestones and proactively communicate risks, blockers, and tradeoffs
• Monitor quality, accuracy, and efficiency, and drive corrective actions when gaps appear
• Recommend the right tools for data collection and labeling, and help shape lightweight in-house tooling or automation where needed
• Facilitate collaboration between engineering and labeling teams to ensure alignment on scope, quality, and timelines
• Own dataset curation workflows end-to-end, including working with production data, public data sources, and external SMEs
• Build and improve long-term labeling processes with a focus on efficiency, latency, accuracy, and scalability

Technical Program Manager, Training Data

Artificial Intelligence

• Work at the intersection of AI product delivery and customer engagement.
• Define, shape, and drive AI-powered solutions that address mission-critical challenges in finance, energy, and government sectors.
• Collaborate closely with data scientists, engineers, and senior stakeholders to translate complex business needs into actionable technical solutions.
• Lead agile delivery cycles, ensure high-quality outcomes, and foster long-term relationships built on trust and impact.

AI Deployment Lead

Machine Learning Engineer

• Innovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.
• Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide.
• Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large.
• Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills.
• Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices.

AI/ML Engineer – Early Career

Full-stack Engineer

• Design, develop, and deploy advanced software solutions that integrate AI to tackle real-world problems
• Interact directly with key customer stakeholders to apply pioneering AI solutions
• Build scalable data pipelines, integrate industrial sensor networks, and optimize application performance
• Stay abreast of developments in software engineering and AI
• Monitor and maintain deployed applications to ensure they continue delivering value