Founding Lead Engineer / Principal Systems Architect

Who We Are

We exist to unlock human potential. Too often, AI drains it—drains budgets, drains energy resources, drains ownership of data. OpenTeams was founded to change that. We build AI that empowers. Our models are energy-efficient, cost-effective, and fully yours. Our ethos is open source. That means freedom, trust, and accountability are built into every line of code. We reinvest 3% of our profits back into the open-source community, because we believe tech is most powerful when it serves everyone. At our core, we value freedom, teamwork, accountability, and uncompromising quality. If you want to challenge the status quo, and shape tools that set people free, OpenTeams is the place to do it.

Founding Lead Engineer / Principal Systems Architect

Evidence-Governed AI/Data Platform

Location: Remote / Hybrid

Employment Type: Full-time

Seniority: Principal / Staff-level

Experience: 8-12+ years preferred, or equivalent exceptional experience

About the Role

We are building a confidential intelligent operations platform for evidence-governed analysis, operational reconstruction, model-assisted workflows, and high-integrity reporting in regulated domains. The first deployment focuses on healthcare integrity, provider-level identity mapping, licensing, ownership, source reconciliation, and defensible review workflows.

We are seeking a hands-on Founding Lead Engineer / Principal Systems Architect to work directly with the concept architect and translate a large, complex system vision into production-grade software, data architecture, model integrations, validation harnesses, and secure Kubernetes-based deployment infrastructure. This is not a standard software engineering role. This is a founding technical role for building the core architecture of a serious AI/data platform from the ground up. The right candidate must be able to absorb abstract system concepts in real time and convert them into schemas, APIs, service boundaries, deployment artifacts, validation tests, and pragmatic engineering roadmaps.

What You Will Build

• canonical identity and entity-resolution services;
• source registry and evidence-management services;
• provider-level healthcare integrity workflows;
• relational, graph, object-store, retrieval, and audit data layers;
• deterministic rules and validation services;
• model-adapter and multi-model routing layers;
• structured-output and model-evaluation workflows;
• human-in-the-loop review workflows;
• graph, timeline, and evidence-review prototypes;
• evidence-linked reporting;
• audit logging and compliance-supporting records;
• secure Kubernetes / cloud / private-infrastructure deployment;
• validation, benchmark, and regression harnesses.

The first deployment will focus on provider-level healthcare integrity. Future deployments may extend into other regulated and high-consequence domains, including legal, financial, AI governance, cyber, public-sector, operational risk, and training/simulation environments.

Key Responsibilities

Concept-to-Code Translation

• Work side-by-side with the concept architect to convert advanced system ideas into technical specifications, service maps, data models, APIs, schemas, tests, and deployment plans.
• Translate verbal and written design guidance into architecture diagrams, implementation backlogs, acceptance criteria, and working prototypes.
• Identify ambiguity, missing assumptions, engineering risks, and unresolved design decisions early, and resolve them before implementation overhead accumulates.