Chief Technology Officer (CFO), Lateral Labs
- Company: Lateral LLC
- Location: Puerto Rico (remote within PR acceptable)
- Compensation & Commitment: We're flexible on structure for the right candidate. Full-time, part-time, or fractional arrangements will all be considered based on your availability and how you want to work with us. Compensation/hourly rate is dependent on experience level and scope of engagement, and will be discussed directly with qualified candidates.
- Reports to: Founder
About Lateral Labs: Lateral Labs is a Puerto Rico–based R&D and software arm of Lateral LLC, a founder-led venture studio.
We are building an AI-enabled management operating system software: workflow orchestration, agentic automation, memory and retrieval systems, permissioning, audit architecture, data integration, and evaluation harnesses all built as real commercial products, not internal tooling. We work from detailed "product constitutions" and executable specs, and we use AI coding tools (Claude Code, Cursor, and similar) as a primary build engine. What we need from you is the architectural judgment that keeps those systems correct, simple, and scalable plus the technical leadership to run a genuine R&D program from Puerto Rico.
The Product: Domain Lateral Labs builds operating systems, in the literal sense, for how companies and principals run:
- MOS (themos.ai): the company operating system. A single, curated source of truth for a company's strategy, goals, org, and policies; kept current by an AI loop that observes the operational tools work actually happens in, proposes precise diffs to the written record, and lets a human ratify every change. The architecture is deliberately bounded: definitional, not operational. MOS holds the definitions; Asana, the CRM, the HRIS, and the ERP hold live state. Strategy cascades through a Goals → Objectives → Approaches → Tactics model down to the work and back, and AI answers are grounded only on the curated, current layer — with sources cited.
- lifeOS : the principal operating system. An AI Chief of Staff for principals who run several lives at once: businesses, property, money, family, legacy. Built around a deliberate asymmetry, one decider at the center, an AI that turns every channel into a decision-ready morning briefing (approve, defer, redirect, decide), staff who supervise the queue, and an outer ring who never log in. An intent cascade connects purpose through eight life domains to today's task. Deployments are single-tenant with append-only, auditable history.
- And more behind them. MOS and lifeOS are the first two products, not the last. Lateral has additional projects queued on the same core. Part of this job is making sure the spine you design carries products we haven't started building yet.
The common architectural spine repeats across the portfolio: a curated entity/definition layer; an observe → propose → ratify reconciliation loop; permission-aware retrieval grounded only on what's true and current; human-in-command approval workflows; append-only audit history; and MCP-native integration with the tools that hold live state. You'll be designing that spine and proving it across the portfolio.
How You Think: The right candidate is a particular kind of thinker, and this matters as much as the stack:
- A product thinker. You bring judgment about what should exist, not just how to build it. You'll challenge a spec when the simpler product answer is better, care about the experience from the seat of the person using it-a CEO, a chief of staff, a principal-and treat "should we build this at all?" as an engineering question.
- An ontologist. You naturally model the world, people, entities, ownership, obligations, decisions, workflows, as a coherent graph, and you know that getting the data model right is most of the product.
- An operator-translator. You understand how businesses are actually run: management cadences, P&L reviews, board reporting, approvals, escalations and can turn those rhythms into software primitives rather than dashboards.
- A platform reductionist. You see that MOS, lifeOS, and the products queued behind them are one system wearing different faces, and you design the shared core instead of parallel codebases.
- A determinist about AI. You treat LLMs as powerful but unreliable components, and you instinctively wrap them in permissions, ratification gates, evaluation, and audit, deterministic scaffolding around probabilistic outputs. In these products, nothing the AI produces enters the record without human approval, and you consider that a feature of the architecture, not a limitation.
- A reconciliation engineer. The hardest problem across the portfolio is keeping a declared truth in sync with observed reality. Detecting drift across email, project tools, CRMs, and calendars, resolving entities, and turning what's changed into precise, human-ratifiable diffs. You find that problem genuinely interesting rather than tedious.
The Role: You will be the technical center of gravity for Lateral Lab and a genuinely product-minded one.
You'll own the architecture of the platform, lead its R&D program from Puerto Rico, build a lean engineering team, and personally build the components where judgment matters most. But you're not executing someone else's spec: you'll pressure-test product constitutions, argue for the simpler product answer, and shape what MOS, lifeOS, and their successors become. This is a high-leverage role for a senior product engineer who wants to build ambitious systems without a big-company org chart around them.
What You'll Do: Architecture & System Design
- Translate product constitutions and business requirements into clean, scalable system architecture
- Design data models, access rules, invariants, and API contracts that hold up as products grow
- Make critical build-vs-wait decisions: what belongs in v1, what gets deferred, what never gets built
- Design the integration layer connecting corporate systems (Paylocity, Jira, financial systems, Google Workspace) into a coherent data layer
- Design the connectivity layer that lets external SaaS tools, partner systems, and internal services plug into the platform via APIs, MCP servers, and webhooks
- Design modular, composable system boundaries so new capabilities can be added without rewriting existing ones
R&D Leadership & Documentation: This is a core part of the job, not an afterthought. Lateral Labs runs a disciplined, documented R&D practice, and the CTO owns it- the thinking, the experiments, and the written record that makes both revisitable.
- Break the platform roadmap into defined R&D projects, each with an identified technical uncertainty
- Define the alternatives to be evaluated and the experiments or prototypes that will resolve each uncertainty
- Document experiments, failed approaches, results, and design decisions as work proceeds
- Produce a concise monthly R&D memo summarizing active projects, findings, and next steps
- Maintain technical decision records so architectural choices are documented and revisitable
- Keep a clear line between exploratory R&D and routine implementation, so the team's energy goes where the uncertainty is highest
AI-Assisted Development Leadership
- Set guardrails and standards for AI-assisted development where automated generation is safe and where human judgment is required
- Review, refactor, and substantially improve AI-generated code to production quality
- Establish reusable patterns, templates, and conventions that AI tools can follow consistently
- Evaluate and integrate emerging AI development tools into the workflow
Hands-On Engineering
- Personally implement critical components: integration layers, data pipelines, security boundaries, core business logic
- Build and maintain MCP servers and API integrations connecting the platform to tools like Asana, Jira, Slack, Salesforce, and Google Workspace
- Build proof-of-concept implementations to validate new capabilities before committing to full builds
Engineering Team Building & Direction
- Recruit and direct a lean engineering team, prioritizing Puerto Rico–based engineers first
- Where specific skills can't be found locally, source overseas engineers for well-defined implementation work; tickets, tests, and modules under your architecture
- Keep the R&D substance: architecture, experiment design, technical decisions in Puerto Rico, with overseas work limited to directed implementation
- Review all engineering code and technical output
- Recommend and evolve the team structure as the roadmap matures
Cross-Product Leverage
- Establish reusable architectural patterns, shared infrastructure, and common libraries across the product portfolio
- Ensure consistency in authentication, authorization, data access, inter-service communication, and external integrations
- Define standard, secure patterns for connecting new external tools and data sources
- Identify opportunities to extract shared capabilities into platform-level services
What You Won't Do
- Run a large organization or sit in recurring status meetings
- Work from vague or undefined requirements
- Over-engineer infrastructure ahead of validated need
- Build pixel-perfect UI from design files
- Write boilerplate code that AI tools can handle
Required Qualifications
- Based in Puerto Rico, or willing to work primarily from Puerto Rico
- 10+ years of software engineering experience with a strong track record of early-stage product architecture and system design
- Product-minded engineering judgment - a track record of shaping what gets built, not just how; able to challenge specs and propose better product answers
- Strong software architecture and data modeling skills - schemas, invariants, and access rules that hold up under real-world complexity
- Demonstrated ability to lead software/AI R&D: framing technical uncertainty, designing experiments, evaluating alternatives, and documenting outcomes
- Hands-on proficiency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or equivalent) and a clear philosophy on using them effectively
- Ability to read, review, and substantially improve AI-generated code - not just accept it
- Full-stack capability with a backend emphasis: API design, data pipelines, infrastructure, frontend integration
- Strong API design and systems integration experience - REST, GraphQL, webhooks, real-time sync, connectors between disparate systems
- Familiarity with LLM application patterns: RAG, agentic workflows, tool-use architectures, prompt engineering
- Working knowledge of MCP (Model Context Protocol) or similar protocol-based interoperability standards
- Experience recruiting, managing, or directing engineering teams, including remote/distributed engineers
- Experience building real commercial software products
- Comfortable operating in a lean, startup, founder-led environment
- Comfortable with clear, consistent written documentation as part of the engineering discipline
Preferred Qualifications
- Founder or 0-to-1 early-stage engineering experience with hard tradeoff decisions under constraint
- Multi-agent system design, orchestration patterns, and protocol-based interoperability (A2A, MCP, or equivalent)
- Hands-on experience building MCP servers or similar integration layers exposing SaaS tools to AI-native platforms
- Familiarity with enterprise SaaS APIs: Paylocity, Jira, Asana, Salesforce, Culture Amp, Slack, or Guru
- Experience consolidating or replacing enterprise SaaS tools with custom-built platforms
- Background in management operating systems, OKR frameworks, FP&A/planning platforms, or corporate strategy tooling
- Experience building work-management, workflow, or vertical "operating system for X" products (e.g., platforms in the mold of Asana, Airtable, Toast, ServiceTitan, Procore)
- Entity/ontology platform experience — modeling organizations, ownership structures, and operational data as a graph (e.g., Palantir Foundry-style forward-deployed or platform work)
- Family office, wealth management, or multi-entity portfolio platform experience
- Experience with security, permissioning, and audit-log architecture
- Experience with evaluation harnesses, regression testing for AI outputs, or human-in-the-loop approval workflows
- Understanding of compliance and data privacy frameworks (SOC 2, etc.)
Working With Us
- You'll work directly with the founder: short feedback loops, fast decisions, no layers between you and the person who can say yes
- The first products are already live and in front of users; you're shaping what they become, not pitching slideware
- Lean by design: AI tools handle volume, you supply judgment
Work Location: Hybrid remote in San Juan, PR 00901
