Founding Lead Engineer / Principal Systems Architect
New
O
OpenTeamsAI Data Platform
U.S - RemoteFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 8-12+ years preferred
- Required Skills
- DockerPostgreSQLPythonSQLKubernetesCI/CDDistributed Systems
Requirements
- 8+ years of professional software engineering experience, or equivalent exceptional experience.
- Expert-level Python engineering.
- Experience building production backend services, APIs, data pipelines, and distributed systems.
- Strong SQL and relational database design experience, preferably PostgreSQL.
- Experience with graph databases, knowledge graphs, or complex relationship modeling.
- Experience with LLM integration, open-weight models, structured outputs, prompt/template management, or model-evaluation workflows.
- Experience with Docker, Kubernetes, Helm, GitOps, CI/CD, and secure cloud or private infrastructure deployment.
- Experience with data validation, audit logging, RBAC, secrets management, and secure software design.
- Ability to design modular systems from ambiguous early-stage architecture.
- Ability to translate non-engineering conceptual guidance into concrete software architecture and implementation plans.
Responsibilities
- 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.
- Build production-grade Python services, APIs, data pipelines, background workers, and orchestration logic.
- Design clean service boundaries for ingestion, entity resolution, evidence management, review workflows, reporting, audit logging, and model integration.
- Design and implement relational schemas, graph models, object-storage structures, retrieval indexes, and audit records.
- Build a model-agnostic adapter layer for open-weight and hosted models.
- Deploy services using Docker, Kubernetes, Helm, GitOps, CI/CD, RBAC, secrets management, and observability.
- Build synthetic datasets, golden tests, regression tests, and benchmark suites.
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